CompSustNet: Publications

Yingheng Wang, Shufeng Kong, John M. Gregoire, Carla P. Gomes (2024). Conformal Crystal Graph Transformer with Robust Encoding of Periodic Invariance. Proceedings of the 38th AAAI Conference on Artificial Intelligence. https://doi.org/10.1609/aaai.v38i1.27781. [pdf]

Marc Grimson, Rafael Almeida, Qinru Shi, Yiwei Bai, Hector Angarita, Felipe Siqueira Pacheco, Rafael Schmitt, Alexander Flecker, Carla P. Gomes (2024). Scaling Up Pareto Optimization for Tree Structures with Affine Transformations: Evaluating Hybrid Floating Solar-Hydropower Systems in the Amazon. Proceedings of the 38th AAAI Conference on Artificial Intelligence. https://doi.org/10.1609/aaai.v38i20.30210. [pdf]

Yimeng Min, Ming-Chiang Chang, Shufeng Kong, John M. Gregoire, R. Bruce van Dover, Michael O. Thompson, Carla P. Gomes (2023). Physically Informed Graph-Based Deep Reasoning Net for Efficient Combinatorial Phase Mapping. 2023 International Conference on Machine Learning and Applications (ICMLA). https://doi.org/10.1109/ICMLA58977.2023.00061.

Yimeng Min, Carla Gomes (2023). Unsupervised Learning Permutations for TSP using Gumbel-Sinkhorn Operator. NeurIPS 2023 Workshop Optimal Transport and Machine Learning. [pdf]

Weitao Du, Yuanqi Du, Limei Wang, Dieqiao Feng, Guifeng Wang, Shuiwang Ji, ... Zhi-Ming Ma (2023). A new perspective on building efficient and expressive 3D equivariant graph neural networks. Advances in Neural Information Processing Systems 36 (NeurIPS 2023). [pdf]

Yuanqi Du, Yingheng Wang, Yining Huang, Jianan Canal Li, Yanqiao Zhu, Tian Xie, ... Carla P. Gomes (2023). M²Hub: Unlocking the Potential of Machine Learning for Materials Discovery. Advances in Neural Information Processing Systems 36 (NeurIPS 2023). [pdf]

Yimeng Min, Yiwei Bai, Carla P. Gomes (2023). Unsupervised Learning for Solving the Travelling Salesman Problem. Advances in Neural Information Processing Systems 36 (NeurIPS 2023). [pdf]

Jeremy M. Cohen, Daniel Fink, Benjamin Zuckerberg (2023). Spatial and seasonal variation in thermal sensitivity within North American bird species. Proceedings of the Royal Society B: Biological Sciences. https://doi.org/10.1098/rspb.2023.1398. [pdf]

Courtney L. Davis, Yiwei Bai, Di Chen, Orin Robinson, Viviana Ruiz-Gutierrez, Carla P. Gomes, Daniel Fink (2023). Deep learning with citizen science data enables estimation of species diversity and composition at continental extents. Ecology. https://doi.org/10.1002/ecy.4175.

Renee Mirka, Laura Greenstreet, Marc Grimson, Carla P. Gomes (2023). A New Approach to Finding 2 x n Partially Spatially Balanced Latin Rectangles (Short Paper). CP 2023. https://doi.org/10.4230/LIPIcs.CP.2023.47.

Shufeng Kong, Caihua Liu, Carla P. Gomes (2023). IPGPT: Solving Integer Programming Problems with Sequence to Contrastive Multi-Label Learning. STRL@IJCAI. [pdf]

Laura Greenstreet, Joshua Fan, Felipe Siqueira Pacheco, Yiwei Bai, Marta Eichemberger Ummus, Carolina Doria, ... Carla P Gomes (2023). Detecting Aquaculture with Deep Learning in a Low-Data Setting. KDD 2023 Fragile Earth Workshop. [pdf]

Hanchen Wang, Tianfan Fu, Yuanqi Du, Wenhao Gao, Kexin Huang, Ziming Liu, ... Marinka Zitnik (2023). Scientific discovery in the age of artificial intelligence. Nature. https://doi.org/10.1038/s41586-023-06221-2.

Dieqiao Feng, Yuanqi Du, Carla P Gomes, Bart Selman (2023). Weighted Sampling without Replacement for Deep Top-k Classification. ICML. [pdf]

Allison D. Binley, Joseph R. Bennett, Richard Schuster, Amanda D. Rodewald, Frank A. La Sorte, Daniel Fink, ... Scott Wilson (2023). Species traits drive responses of forest birds to agriculturally-modified habitats throughout the annual cycle. Ecography. https://doi.org/10.1111/ecog.06457. [pdf]

Jinzhao Li, Daniel Fink, Christopher Wood, Carla P. Gomes, Yexiang Xue (2023). Provable Optimization of Quantal Response Leader-Follower Games with Exponentially Large Action Spaces. AAMAS '23: Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems.

Yiwei Bai, Qinru Shi, Marc Grimson, Alexander Flecker, Carla P. Gomes (2023). Efficiently Approximating High-Dimensional Pareto Frontiers for Tree-Structured Networks Using Expansion and Compression. CPAIOR. https://doi.org/10.1007/978-3-031-33271-5_1.

Tinghan Ye, David B. Shmoys (2023). A min-max theorem for the minimum fleet-size problem. Operations Research Letters. https://doi.org/10.1016/j.orl.2023.03.013.

Olivia J. Graham, Tiffany Stephens, Brendan Rappazzo, Corinne Klohmann, Sukanya Dayal, Emily M. Adamczyk, ... Drew Harvell (2023). Deeper habitats and cooler temperatures moderate a climate-driven seagrass disease. Philosophical Transactions of the Royal Society B: Biological Sciences. https://doi.org/10.1098/rstb.2022.0016.

Miguel Fuentes, Benjamin M. Van Doren, Daniel Fink, Daniel Sheldon (2023). BirdFlow: Learning seasonal bird movements from eBird data. Methods in Ecology and Evolution. https://doi.org/10.1111/2041-210X.14052. [pdf]

Jiayue Wan, Casey L. Cazer, Marin E. Clarkberg, Shane G. Henderson, Scarlett E. Lee, Genevive R. Meredith, ... Peter I. Frazier (2023). Booster vaccination protection against SARS-CoV-2 infections in young adults during an Omicron BA.1-predominant period: A retrospective cohort study. PLOS Medicine. https://doi.org/10.1371/journal.pmed.1004153. [pdf]

Dieqiao Feng, Carla P. Gomes, Bart Selman (2022). Left Heavy Tails and the Effectiveness of the Policy and Value Networks in DNN-based best-first search for Sokoban Planning. Advances in Neural Information Processing Systems 35 (NeurIPS 2022). [pdf]

Junwen Bai, Yuanqi Du, Yingheng Wang, Shufeng Kong, John Gregoire, Carla P Gomes (2022). Xtal2DoS: Attention-based Crystal to Sequence Learning for Density of States Prediction. NeurIPS 2022 AI for Science: Progress and Promises. [pdf]

Gengchen Mai, Chris Cundy, Kristy Choi, Yingjie Hu, Ni Lao, Stefano Ermon (2022). Towards a foundation model for geospatial artificial intelligence (vision paper). SIGSPATIAL '22: Proceedings of the 30th International Conference on Advances in Geographic Information Systems. https://doi.org/10.1145/3557915.3561043. [pdf]

Spencer R. Keyser, Daniel Fink, David Gudex-Cross, Volker C. Radeloff, Jonathan N. Pauli, Benjamin Zuckerberg (2022). Snow cover dynamics: an overlooked yet important feature of winter bird occurrence and abundance across the United States. Ecography. https://doi.org/10.1111/ecog.06378. [pdf]

Devin Smedira, David Shmoys (2022). Scheduling Appointments Online: The Power of Deferred Decision-Making. WAOA 2022: Approximation and Online Algorithms. https://doi.org/10.1007/978-3-031-18367-6_5.

North American Bird Conservation Initiative (2022). The State of the Birds, United States of America, 2022. [pdf]

Martin Kassabov, Steven H. Strogatz, Alex Townsend (2022). A global synchronization theorem for oscillators on a random graph. Chaos. https://doi.org/10.1063/5.0090443.

Joshua Fan, Di Chen, Jiaming Wen, Ying Sun, Carla Gomes (2022). Monitoring Vegetation From Space at Extremely Fine Resolutions via Coarsely-Supervised Smooth U-Net. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence: AI for Good. https://doi.org/10.24963/ijcai.2022/703 . arXiv: 2207.08022. [pdf]

Rachit Agarwal, Shijin Rajakrishnan, David B. Shmoys (2022). From Switch Scheduling to Datacenter Scheduling: Matching-Coordinated Greed is Good. PODC'22: Proceedings of the 2022 ACM Symposium on Principles of Distributed Computing. https://doi.org/10.1145/3519270.3538443.

Sebastian E Ament, Carla P Gomes (2022). Scalable First-Order Bayesian Optimization via Structured Automatic Differentiation. Proceedings of the 39th International Conference on Machine Learning, PMLR. arXiv: 2206.08366. [pdf]

Junwen Bai, Shufeng Kong, Carla P Gomes (2022). Gaussian Mixture Variational Autoencoder with Contrastive Learning for Multi-Label Classification. Proceedings of the 39th International Conference on Machine Learning, PMLR. arXiv: 2112.00976. [pdf]

Jiaming Song, Lantao Yu, Willie Neiswanger, Stefano Ermon (2022). A General Recipe for Likelihood-free Bayesian Optimization. Proceedings of the 39th International Conference on Machine Learning, PMLR. [pdf]

Joshua Fan, Junwen Bai, Zhiyun Li, Ariel Ortiz-Bobea, Carla P. Gomes (2022). A GNN-RNN Approach for Harnessing Geospatial and Temporal Information: Application to Crop Yield Prediction. Proceedings of the AAAI Conference on Artificial Intelligence. https://doi.org/10.1609/aaai.v36i11.21444. arXiv: 2111.08900. [pdf]

Niko A. Grupen, Bart Selman, Daniel D. Lee (2022). Cooperative Multi-Agent Fairness and Equivariant Policies. Proceedings of the AAAI Conference on Artificial Intelligence. https://doi.org/10.1609/aaai.v36i9.21166. [pdf]

Chenlin Meng, Enci Liu, Willie Neiswanger, Jiaming Song, Marshall Burke, David Lobell, Stefano Ermon (2022). IS-Count: Large-Scale Object Counting from Satellite Images with Covariate-Based Importance Sampling. Proceedings of the AAAI Conference on Artificial Intelligence. https://doi.org/10.1609/aaai.v36i11.21462 . [pdf]

Daniel Freund, Shane G. Henderson, David B. Shmoys (2022). Minimizing Multimodular Functions and Allocating Capacity in Bike-Sharing Systems. Operations Research. https://doi.org/10.1287/opre.2022.2320.

Samarth Sinha, Jiaming Song, Animesh Garg, Stefano Ermon (2022). Experience Replay with Likelihood-free Importance Weights. Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR. [pdf]

Rafael M. Almeida, Rafael Schmitt, Steven M. Grodsky, Alexander S. Flecker, Carla P. Gomes, Lu Zhao, ... Peter B. McIntyre (2022). Floating solar power could help fight climate change — let's get it right. Nature. https://doi.org/10.1038/d41586-022-01525-1.

Rafael M Almeida, Rafael JP Schmitt, Andrea Castelletti, Alexander S Flecker, Julien J Harou, Sebastian A Heilpern, ... Peter B McIntyre (2022). Strategic planning of hydropower development: balancing benefits and socioenvironmental costs. Current Opinion in Environmental Sustainability. https://doi.org/10.1016/j.cosust.2022.101175.

Lillian R. Aoki, Brendan Rappazzo, Deanna S. Beatty, Lia K. Domke, Ginny L. Eckert, Morgan E. Eisenlord, ... C. Drew Harvell (2022). Disease surveillance by artificial intelligence links eelgrass wasting disease to ocean warming across latitudes. Limnology and Oceanography. https://doi.org/10.1002/lno.12152.

Sebastian Ament, Carla Gomes (2022). Generalized Matching Pursuits for the Sparse Optimization of Separable Objectives. 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). https://doi.org/10.1109/ICASSP43922.2022.9747510.

Niko A. Grupen, Daniel D. Lee, Bart Selman (2022). Multi-Agent Curricula and Emergent Implicit Signaling. Proc. of the 21st International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2022) [pdf]

Johan Bjorck, Carla P Gomes, Kilian Q Weinberger (2022). Is High Variance Unavoidable in RL? A Case Study in Continuous Control. The Tenth International Conference on Learning Representations. arXiv: 2110.11222. [pdf]

Chenlin Meng, Yutong He, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, Stefano Ermon (2022). SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations. The Tenth International Conference on Learning Representations (ICLR 2022).

Yang Song, Liyue Shen, Lei Xing, Stefano Ermon (2022). Solving Inverse Problems in Medical Imaging with Score-Based Generative Models. The Tenth International Conference on Learning Representations (ICLR 2022).

Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, Jian Tang (2022). GeoDiff: A Geometric Diffusion Model for Molecular Conformation Generation. The Tenth International Conference on Learning Representations (ICLR 2022).

Shengjia Zhao, Abhishek Sinha, Yutong He, Aidan Perreault, Jiaming Song, Stefano Ermon (2022). Comparing Distributions by Measuring Differences that Affect Decision Making. The Tenth International Conference on Learning Representations (ICLR 2022).

Warren B. Powell (2022). Reinforcement Learning and Stochastic Optimization: A Unified Framework for Sequential Decisions. https://doi.org/10.1002/9781119815068.

John P. Ryan, Sebastian E. Ament, Carla P. Gomes, Anil Damle (2022). The Fast Kernel Transform. Proceedings of The 25th International Conference on Artificial Intelligence and Statistics, PMLR. arXiv: 2106.04487. [pdf]

Kristy Choi, Chenlin Meng, Yang Song, Stefano Ermon (2022). Density Ratio Estimation via Infinitesimal Classification . Proceedings of The 25th International Conference on Artificial Intelligence and Statistics, PMLR. [pdf]

Frank A. La Sorte, Kyle G. Horton, Alison Johnston, Daniel Fink, Tom Auer (2022). Seasonal associations with light pollution trends for nocturnally migrating bird populations. Ecosphere. https://doi.org/10.1002/ecs2.3994. [pdf]

Frank A. La Sorte, Alison Johnston, Amanda D. Rodewald, Daniel Fink, Andrew Farnsworth, Benjamin M. Van Doren, ... Matthew Strimas-Mackey (2022). The role of artificial light at night and road density in predicting the seasonal occurrence of nocturnally migrating birds. Diversity and Distributions. https://doi.org/10.1111/ddi.13499.

Wee Hao Ng, Daniel Fink, Frank A. La Sorte, Tom Auer, Wesley M. Hochachka, Alison Johnston, Adriaan M. Dokter (2022). Continental-scale biomass redistribution by migratory birds in response to seasonal variation in productivity. Global Ecology and Biogeography. https://doi.org/10.1111/geb.13460.

Alexander S. Flecker, Qinru Shi, Rafael M. Almeida, Héctor Angarita, Jonathan M. Gomes-Selman, Roosevelt García-Villacorta, ... Carla P. Gomes (2022). Reducing adverse impacts of Amazon hydropower expansion. Science. https://doi.org/10.1126/science.abj4017.

Scott Wilson, Hsien-Yung Lin, Richard Schuster, Ana M. González, Camila Gómez, Esteban Botero-Delgadillo, ... Viviana Ruiz Gutierrez (2021). Opportunities for the conservation of migratory birds to benefit threatened resident vertebrates in the Neotropics. Journal of Applied Ecology. https://doi.org/10.1111/1365-2664.14077.

Olivia J. Graham, Lillian R. Aoki, Tiffany Stephens, Joshua Stokes, Sukanya Dayal, Brendan Rappazzo, ... C. Drew Harvell (2021). Effects of Seagrass Wasting Disease on Eelgrass Growth and Belowground Sugar in Natural Meadows. Frontiers in Marine Science. https://doi.org/10.3389/fmars.2021.768668.

Rafael M. Almeida, Ayan S. Fleischmann, João P.F. Brêda, Diego S. Cardoso, Hector Angarita, Walter Collischonn, ... Alexander S. Flecker (2021). Climate change may impair electricity generation and economic viability of future Amazon hydropower. Global Environmental Change. https://doi.org/10.1016/j.gloenvcha.2021.102383.

Yiewi Bai, Di Chen, Carla P. Gomes (2021). CLR-DRNets: Curriculum Learning with Restarts to Solve Visual Combinatorial Games. 27th International Conference on Principles and Practice of Constraint Programming (CP 2021). https://doi.org/10.4230/LIPIcs.CP.2021.17. [pdf]

Eric Che, Abdul-Aziz Yakubu (2021). A discrete-time risk-structured model of cholera infections in Cameroon. Journal of Biological Dynamics. https://doi.org/10.1080/17513758.2021.1991497.

Abdul-Aziz Yakubu (2021). A discrete-time infectious disease model for global pandemics. PNAS. https://doi.org/10.1073/pnas.2116845118.

Kumar Ayush, Burak Uzkent, Chenlin Meng, Kumar Tanmay, Marshall Burke, David Lobell, Stefano Ermon (2021). Geography-Aware Self-Supervised Learning. Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV).

Eric Che, Eric Numfor, Suzanne Lenhart, Abdul-Aziz Yakubu (2021). Mathematical modeling of the influence of cultural practices on cholera infections in Cameroon. Mathematical Biosciences and Engineering. https://doi.org/10.3934/mbe.2021415.

Di Chen, Yiwei Bai, Sebastian Ament, Wenting Zhao, Dan Guevarra, Lan Zhou, ... Carla P. Gomes (2021). Automating crystal-structure phase mapping by combining deep learning with constraint reasoning. Nature Machine Intelligence. https://doi.org/10.1038/s42256-021-00384-1. arXiv: 2108.09523.

Cover article

Bingqing Chen, Priya L. Donti, Kyri Baker, J. Zico Kolter, Mario Bergés (2021). Enforcing Policy Feasibility Constraints through Differentiable Projection for Energy Optimization. e-Energy '21: Proceedings of the Twelfth ACM International Conference on Future Energy Systems. https://doi.org/10.1145/3447555.3464874.

Benjamin M. Van Doren, David E. Willard, Mary Hennen, Kyle G. Horton, Erica F. Stuber, Daniel Sheldon, ... Benjamin M. Winger (2021). Drivers of fatal bird collisions in an urban center. PNAS. https://doi.org/10.1073/pnas.2101666118.

Sebastian Ament, Carla Gomes (2021). On the Optimality of Backward Regression: Sparse Recovery and Subset Selection. International Conference on Acoustics, Speech, and Signal Processing (ICASSP). https://doi.org/10.1109/ICASSP39728.2021.9415082.

Omar El Housni, Vineet Goyal, David Shmoys (2021). On the Power of Static Assignment Policies for Robust Facility Location Problems. Integer Programming and Combinatorial Optimization (IPCO). https://doi.org/10.1007/978-3-030-73879-2_18.

Johan Bjorck, Anmol Kabra, Kilian Q. Weinberger, Carla P. Gomes (2021). Characterizing the Loss Landscape in Non-Negative Matrix Factorization. Proceedings of the AAAI Conference on Artificial Intelligence. [pdf]

Johan Bjorck, Kilian Q. Weinberger, Carla P. Gomes (2021). Understanding Decoupled and Early Weight Decay. Proceedings of the AAAI Conference on Artificial Intelligence. [pdf]

Johan Bjorck, Qinru Shi, Carrie Brown-Lima, Jennifer Dean, Angela Fuller, Carla P. Gomes (2021). Learning Augmented Methods for Matching: Improving Invasive Species Management and Urban Mobility. Proceedings of the AAAI Conference on Artificial Intelligence. [pdf]

Johan Bjorck, Brendan H. Rappazzo, Qinru Shi, Carrie Brown-Lima, Jennifer Dean, Angela Fuller, Carla P. Gomes (2021). Accelerating Ecological Sciences from Above: Spatial Contrastive Learning for Remote Sensing. Proceedings of the AAAI Conference on Artificial Intelligence. [pdf]

Wenting Zhao, Shufeng Kong, Junwen Bai, Daniel Fink, Carla P. Gomes (2021). HOT-VAE: Learning High-Order Label Correlation for Multi-Label Classification via Attention-Based Variational Autoencoders. Proceedings of the AAAI Conference on Artificial Intelligence. [pdf]

Brendan H. Rappazzo, Morgan E. Eisenlord, Olivia J. Graham, Lillian R. Aoki, Phoebe D. Dawkins, Drew Harvell, Carla P. Gomes (2021). EeLISA: Combating Global Warming Through the Rapid Analysis of Eelgrass Wasting Disease. Proceedings of the AAAI Conference on Artificial Intelligence. [pdf]

Kumar Ayush, Burak Uzkent, Kumar Tanmay, Marshall Burke, David B. Lobell, Stefano Ermon (2021). Efficient Poverty Mapping from High Resolution Remote Sensing Images. Proceedings of the AAAI Conference on Artificial Intelligence. [pdf]

Jihyeon Janel Lee, Dylan Grosz, Burak Uzkent, Sicheng Zeng, Marshall Burke, David B. Lobell, Stefano Ermon (2021). Predicting Livelihood Indicators from Community-Generated Street-Level Imagery. Proceedings of the AAAI Conference on Artificial Intelligence. [pdf]

Alison Johnston, Wesley M. Hochachka, Matthew E. Strimas-Mackey, Viviana Ruiz Gutierrez, Orin J. Robinson, Eliot T. Miller, ... Daniel Fink (2021). Analytical guidelines to increase the value of community science data: An example using eBird data to estimate species distributions. Diversity and Distributions. https://doi.org/10.1111/ddi.13271.

Ashwin H. Sivakumar, Daniel Sheldon, Kevin Winner, Carolyn S. Burt, Kyle G. Horton (2021). A weather surveillance radar view of Alaskan avian migration. Proceedings of the Royal Society B. https://doi.org/10.1098/rspb.2021.0232.

Jeremy M. Cohen, Daniel Fink, Benjamin Zuckerberg (2021). Extreme winter weather disrupts bird occurrence and abundance patterns at geographic scales. Ecography. https://doi.org/10.1111/ecog.05495.

Yilun Xu, Yang Song, Sahaj Garg, Linyuan Gong, Rui Shu, Aditya Grover, Stefano Ermon (2021). Anytime Sampling for Autoregressive Models via Ordered Autoencoding. International Conference on Learning Representations.

Abhishek Sinha, Kumar Ayush, Jiaming Song, Burak Uzkent, Hongxia Jin, Stefano Ermon (2021). Negative Data Augmentation. International Conference on Learning Representations.

Chenlin Meng, Jiaming Song, Yang Song, Shengjia Zhao, Stefano Ermon (2021). Improved Autoregressive Modeling with Distribution Smoothing. International Conference on Learning Representations.

Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, Ben Poole (2021). Score-Based Generative Modeling through Stochastic Differential Equations. International Conference on Learning Representations.

Priya L. Donti, David Rolnick, J Zico Kolter (2021). DC3: A learning method for optimization with hard constraints. International Conference on Learning Representations.

Priya L. Donti, Melrose Roderick, Mahyar Fazlyab, J Zico Kolter (2021). Enforcing robust control guarantees within neural network policies. International Conference on Learning Representations.

Han-Ching Ou, Haipeng Chen, Shahin Jabbari, Milind Tambe (2021). Active Screening for Recurrent Diseases: A Reinforcement Learning Approach. Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS '21). arXiv: 2101.02766. [pdf]

Jihyeon Lee, Nina R. Brooks, Fahim Tajwar, Marshall Burke, Stefano Ermon, David B. Lobell, ... Stephen P. Luby (2021). Scalable deep learning to identify brick kilns and aid regulatory capacity. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.2018863118.

Janice Brahney, Natalie Mahowald, Marje Prank, Gavin Cornwell, Zbigniew Klimont, Hitoshi Matsui, Kimberly Ann Prather (2021). Constraining the atmospheric limb of the plastic cycle. PNAS. https://doi.org/10.1073/pnas.2020719118.

Mohit Yadav, Daniel Sheldon, Cameron Musco (2021). Faster Kernel Interpolation for Gaussian Processes. Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR.

Shengjia Zhao, Stefano Ermon (2021). Right Decisions from Wrong Predictions: A Mechanism Design Alternative to Individual Calibration. Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR.

Kyle G. Horton, Benjamin M. Van Doren, Heidi J. Albers, Andrew Farnsworth, Daniel Sheldon (2021). Near-term ecological forecasting for dynamic aeroconservation of migratory birds. Conservation Biology. https://doi.org/10.1111/cobi.13740.

Marshall Burke, Anne Driscoll, David B. Lobell, Stefano Ermon (2021). Using satellite imagery to understand and promote sustainable development. Science. https://doi.org/10.1126/science.abe8628.

David Gudex-Cross, Spencer R. Keyser, Benjamin Zuckerberg, Daniel Fink, Likai Zhu, Jonathan N. Pauli, Volker C. Radeloff (2021). Winter Habitat Indices (WHIs) for the contiguous US and their relationship with winter bird diversity. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2021.112309.

Viviana Ruiz-Gutierrez, Emily R. Bjerre, Mark C. Otto, Guthrie S. Zimmerman, Brian A. Millsap, Daniel Fink, ... Orin J. Robinson (2021). A pathway for citizen science data to inform policy: A case study using eBird data for defining low-risk collision areas for wind energy development. Journal of Applied Ecology. https://doi.org/10.1111/1365-2664.13870.

Joshua Williams, J. Zico Kolter (2021). A Bayesian Model of Cash Bail Decisions. FAccT '21: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency. https://doi.org/10.1145/3442188.3445908.

M. R. S. KulenoviĆ, M. NurkanoviĆ, Abdul-Aziz Yakubu (2021). Asymptotic behavior of a discrete-time density-dependent SI epidemic model with constant recruitment. Journal of Applied Mathematics and Computing. https://doi.org/10.1007/s12190-021-01503-2.

Wesley M. Hochachka, Hany Alonso, Carlos Gutiérrez-Expósito, Eliot Miller, Alison Johnston (2021). Regional variation in the impacts of the COVID-19 pandemic on the quantity and quality of data collected by the project eBird. Biological Conservation. https://doi.org/10.1016/j.biocon.2021.108974.

Michelle Y. Wong, Sagar D. Rathod, Roxanne Marino, Longlei Li, Robert W. Howarth, Andres Alastuey, ... Natalie M. Mahowald (2021). Anthropogenic Perturbations to the Atmospheric Molybdenum Cycle. Global Biogeochemical Cycles. https://doi.org/10.1029/2020GB006787.

Tessa B. Francis, Karen C. Abbott, Kim Cuddington, Gabriel Gellner, Alan Hastings, Ying-Cheng Lai, ... Mary Lou Zeeman (2021). Management implications of long transients in ecological systems. Nature Ecology & Evolution. https://doi.org/10.1038/s41559-020-01365-0.

Niko A. Grupen, Daniel D. Lee, Bart Selman (2020). Low-Bandwidth Communication Emerges Naturally in Multi-Agent Learning Systems. Talking to Strangers: Zero-Shot Emergent Communication Workshop NeurIPS 2020. arXiv: 2011.14890.

Dieqiao Feng, Carla P. Gomes, Bart Selman (2020). A Novel Automated Curriculum Strategy to Solve Hard Sokoban Planning Instances. Advances in Neural Information Processing Systems 33 (NeurIPS). [pdf]

Chenlin Meng, Lantao Yu, Yang Song, Jiaming Song, Stefano Ermon (2020). Autoregressive Score Matching. Advances in Neural Information Processing Systems 33 (NeurIPS). [pdf]

Jonathan Kuck, Shuvam Chakraborty, Hao Tang, Rachel Luo, Jiaming Song, Ashish Sabharwal, Stefano Ermon (2020). Belief Propagation Neural Networks. Advances in Neural Information Processing Systems 33 (NeurIPS). [pdf]

Yusuke Tashiro, Yang Song, Stefano Ermon (2020). Diversity can be Transferred: Output Diversification for White- and Black-box Attacks. Advances in Neural Information Processing Systems 33 (NeurIPS). [pdf]

Yang Song, Stefano Ermon (2020). Improved Techniques for Training Score-Based Generative Models. Advances in Neural Information Processing Systems 33 (NeurIPS). [pdf]

Jiaming Song, Stefano Ermon (2020). Multi-label Contrastive Predictive Coding. Advances in Neural Information Processing Systems 33 (NeurIPS). [pdf]

Andy Shih, Stefano Ermon (2020). Probabilistic Circuits for Variational Inference in Discrete Graphical Models. Advances in Neural Information Processing Systems 33 (NeurIPS). [pdf]

Emily B. Cohen, Kyle G. Horton, Peter P. Marra, Hannah L. Clipp, Andrew Farnsworth, Jaclyn A. Smolinsky, ... Jeffrey J. Buler (2020). A place to land: spatiotemporal drivers of stopover habitat use by migrating birds. Ecology Letters. https://doi.org/10.1111/ele.13618.

Bryan Wilder, Sze-chuan Suen, Milind Tambe (2020). Allocating outreach resources for disease control in a dynamic population with information spread. IISE Transactions. https://doi.org/10.1080/24725854.2020.1798037.

Shengjia Zhao, Christopher Yeh, Stefano Ermon (2020). A Framework for Sample Efficient Interval Estimation with Control Variates. Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics (AISTATS). [pdf]

Chenhao Niu, Yang Song, Jiaming Song, Shengjia Zhao, Aditya Grover, Stefano Ermon (2020). Permutation Invariant Graph Generation via Score-Based Generative Modeling. Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics (AISTATS). [pdf]

Chenlin Meng, Yang Song, Jiaming Song, Stefano Ermon (2020). Gaussianization Flows. Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics (AISTATS). [pdf]

Travis Moore, Weng-Keen Wong (2020). The Quantile Snapshot Scan: Comparing Quantiles of Spatial Data from Two Snapshots in Time. Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics (AISTATS). [pdf]

Elizabeth Bondi, Andrew Perrault, Fei Fang, Benjamin Rice, Christopher Golden, Milind Tambe (2020). Mapping for Public Health: Initial Plan for Using Satellite Imagery for Micronutrient Deficiency Prediction. KDD Humanitarian Mapping Workshop.

Alex Townsenda, Michael Stillman, Steven H. Strogatz (2020). Dense networks that do not synchronize and sparse ones that do. Chaos. https://doi.org/10.1063/5.0018322.

Chris Cundy, Stefano Ermon (2020). Flexible Approximate Inference via Stratified Normalizing Flows. Uncertainty in Artificial Intelligence (UAI 2020). [pdf]

Eric Lee, David Eriksson, David Bindel, Bolong Cheng, Mike Mccourt (2020). Efficient Rollout Strategies for Bayesian Optimization. Uncertainty in Artificial Intelligence (UAI 2020). [pdf]

Nathan Jensen, Elizabeth Lyons, Eddy Chebelyon, Ronan Le Bras, Carla Gomes (2020). Conspicuous monitoring and remote work. Journal of Economic Behavior & Organization. https://doi.org/10.1016/j.jebo.2020.05.010.

Rafael M. Almeida, Stephen K. Hamilton, Emma J. Rosi, Nathan Barros, Carolina R. C. Doria, Alexander S. Flecker, ... Fábio Roland (2020). Hydropeaking Operations of Two Run-of-River Mega-Dams Alter Downstream Hydrology of the Largest Amazon Tributary. Frontiers in Environmental Science. https://doi.org/10.3389/fenvs.2020.00120.

Di Chen, Yiwei Bai, Wenting Zhao, Sebastian Ament, John Gregoire, Carla Gomes (2020). Deep Reasoning Networks for Unsupervised Pattern De-mixing with Constraint Reasoning. ICML. [pdf]

Shengjia Zhao, Tengyu Ma, Stefano Ermon (2020). Individual Calibration with Randomized Forecasting. ICML. [pdf]

Lantao Yu, Yang Song, Jiaming Song, Stefano Ermon (2020). Training Deep Energy-Based Models with f-Divergence Minimization. ICML. [pdf]

Jiaming Song, Stefano Ermon (2020). Bridging the Gap Between f-GANs and Wasserstein GANs. ICML. [pdf]

Kuno Kim, Yihong Gu, Jiaming Song, Shengjia Zhao, Stefano Ermon (2020). Domain Adaptive Imitation Learning. ICML. [pdf]

Kristy Choi, Aditya Grover, Trisha Singh, Rui Shu, Stefano Ermon (2020). Fair Generative Modeling via Weak Supervision. ICML. [pdf]

Ian Delbridge, David Bindel, Andrew Gordon Wilson (2020). Randomly Projected Additive Gaussian Processes for Regression. ICML. [pdf]

Shufeng Kong, Junwen Bai, Jae Hee Lee, Di Chen, Andrew Allyn, Michelle Stuart, ... Carla Gomes (2020). Deep Hurdle Networks for Zero-Inflated Multi-Target Regression: Application to Multiple Species Abundance Estimation. Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence Special track on AI for CompSust and Human well-being. https://doi.org/10.24963/ijcai.2020/603. [pdf]

Dieqiao Feng, Carla Gomes, Bart Selman (2020). Solving Hard AI Planning Instances Using Curriculum-Driven Deep Reinforcement Learning. Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence Main track. https://doi.org/10.24963/ijcai.2020/304. [pdf]

Junwen Bai, Shufeng Kong, Carla Gomes (2020). Disentangled Variational Autoencoder based Multi-Label Classification with Covariance-Aware Multivariate Probit Model. Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence Special track on AI for CompSust and Human well-being. https://doi.org/10.24963/ijcai.2020/595. [pdf]

Kumar Ayush, Burak Uzkent, Marshall Burke, David Lobell, Stefano Ermon (2020). Generating Interpretable Poverty Maps using Object Detection in Satellite Images. Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence Special track on AI for CompSust and Human well-being. https://doi.org/10.24963/ijcai.2020/608. [pdf]

Di Chen, Yada Zhu, Xiaodong Cui, Carla Gomes (2020). Task-Based Learning via Task-Oriented Prediction Network with Applications in Finance. Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence Special Track on AI in FinTech. https://doi.org/10.24963/ijcai.2020/617. [pdf]

Jonas S. Juul, Steven H. Strogatz (2020). Descendant distributions for the impact of mutant contagion on networks. Physical Review Research. https://doi.org/10.1103/PhysRevResearch.2.033005.

Nourridine Siewe, Suzanne Lenhart, Abdul-Aziz Yakubu (2020). Ebola Outbreaks and International Travel Restrictions: Case Studies of Central and West Africa Regions. Journal of Biological Systems. https://doi.org/10.1142/S0218339020400070.

Tadesse ZeMicheal, Thomas G. Dietterich (2020). Conditional mixture models for precipitation data quality control. COMPASS '20: Proceedings of the 3rd ACM SIGCAS Conference on Computing and Sustainable Societies. https://doi.org/10.1145/3378393.3403823. [pdf]

Taoan Huang, Bistra Dilkina (2020). Enhancing Seismic Resilience of Water Pipe Networks. COMPASS '20: Proceedings of the 3rd ACM SIGCAS Conference on Computing and Sustainable Societies. https://doi.org/10.1145/3378393.3402246. [pdf]

Burak Uzkent, Stefano Ermon (2020). Learning When and Where to Zoom With Deep Reinforcement Learning. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). https://doi.org/10.1109/CVPR42600.2020.01236.

Jeremy M. Cohen, Daniel Fink, Benjamin Zuckerberg (2020). Avian responses to extreme weather across functional traits and temporal scales. Global Change Biology. https://doi.org/10.1111/gcb.15133.

Christopher Yeh, Anthony Perez, Anne Driscoll, George Azzari, Zhongyi Tang, David Lobell, ... Marshall Burke (2020). Using publicly available satellite imagery and deep learning to understand economic well-being in Africa. Nature Communications. https://doi.org/10.1038/s41467-020-16185-w.

Tim Coleman, Lucas Mentch, Daniel Fink, Frank A. La Sorte, David W. Winkler, Giles Hooker, Wesley M. Hochachka (2020). Statistical inference on tree swallow migrations with random forests. Journal of the Royal Statistical Society: Series C (Applied Statistics). https://doi.org/10.1111/rssc.12416.

Elizabeth Bondi (2020). Vision for Decisions: Utilizing Uncertain Real-Time Information and Signaling for Conservation. AAMAS '20: Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems.

Alice Paul, Daniel Freund, Aaron Ferber, David B. Shmoys, David P. Williamson (2020). Budgeted Prize-Collecting Traveling Salesman and Minimum Spanning Tree Problems. Mathematics of Operations Research. https://doi.org/10.1287/moor.2019.1002.

Yilun Xu, Shengjia Zhao, Jiaming Song, Russell Stewart, Stefano Ermon (2020). A Theory of Usable Information under Computational Constraints. 8th International Conference on Learning Representations, ICLR 2020. [pdf]

Jiaming Song, Stefano Ermon (2020). Understanding the Limitations of Variational Mutual Information Estimators. 8th International Conference on Learning Representations, ICLR 2020. [pdf]

Gonçalo C. Cardoso, Brian T. Klingbeil, Frank A. La Sorte, Christopher A. Lepczyk, Daniel Fink, Curtis H. Flather (2020). Exposure to noise pollution across North American passerines supports the noise filter hypothesis. Global Ecology and Biogeography. https://doi.org/10.1111/geb.13085.

Burak Uzkent, Christopher Yeh, Stefano Ermon (2020). Efficient Object Detection in Large Images Using Deep Reinforcement Learning. 2020 IEEE Winter Conference on Applications of Computer Vision (WACV). https://doi.org/10.1109/WACV45572.2020.9093447.

Vishnu Sarukkai, Anirudh Jain, Burak Uzkent, Stefano Ermon (2020). Cloud Removal in Satellite Images Using Spatiotemporal Generative Networks. 2020 IEEE Winter Conference on Applications of Computer Vision (WACV). https://doi.org/10.1109/WACV45572.2020.9093564.

Elizabeth Bondi, Raghav Jain, Palash Aggrawal, Saket Anand, Robert Hannaford, Ashish Kapoor, ... Milind Tambe (2020). BIRDSAI: A Dataset for Detection and Tracking in Aerial Thermal Infrared Videos. 2020 IEEE Winter Conference on Applications of Computer Vision (WACV). https://doi.org/10.1109/WACV45572.2020.9093284.

Caleb Robinson, Anthony Ortiz, Kolya Malkin, Blake Elias, Andi Peng, Dan Morris, ... Nebojsa Jojic (2020). Human-Machine Collaboration for Fast Land Cover Mapping. AAAI-20. https://doi.org/10.1609/aaai.v34i03.5633. [pdf]

Elizabeth Bondi, Hoon Oh, Haifeng Xu, Fei Fang, Bistra Dilkina, Milind Tambe (2020). To Signal or Not To Signal: Exploiting Uncertain Real-Time Information in Signaling Games for Security and Sustainability. AAAI-20. https://doi.org/10.1609/aaai.v34i02.5493. [pdf]

Mike Wu, Kristy Choi, Noah Goodman, Stefano Ermon (2020). Meta-Amortized Variational Inference and Learning. AAAI-20. https://doi.org/10.1609/aaai.v34i04.6111. [pdf]

Zezhou Cheng, Saadia Gabriel, Pankaj Bhambhani, Daniel Sheldon, Subhransu Maji, Andrew Laughlin, David Winkler (2020). Detecting and Tracking Communal Bird Roosts in Weather Radar Data. AAAI-20. https://doi.org/10.1609/aaai.v34i01.5373.

Jon M. Conrad, Daniel Rondeau (2020). Natural Resource Economics: Analysis, Theory, and Applications. https://doi.org/10.1017/9781108588928.

Abdul-Aziz Yakubu (2020). Demographic Population Cycles in Infectious Salmon Anemia Models. Notices of the AMS. https://doi.org/10.1090/noti2015.

Eric Ngang Che, Yeona Kang, Abdul-Aziz Yakubu (2020). Risk structured model of cholera infections in Cameroon. Mathematical Biosciences. https://doi.org/10.1016/j.mbs.2019.108303.

Caleb Robinson, Bistra Dilkina, Juan Moreno-Cruz (2020). Modeling migration patterns in the USA under sea level rise. PLOS ONE. https://doi.org/10.1371/journal.pone.0227436. arXiv: 1904.10160.

Kyle G. Horton, Frank A. La Sorte, Daniel Sheldon, Tsung-Yu Lin, Kevin Winner, Garrett Bernstein, ... Andrew Farnsworth (2019). Phenology of nocturnal avian migration has shifted at the continental scale. Nature Climate Change. https://doi.org/10.1038/s41558-019-0648-9.

A. Johnston, T. Auer, D. Fink, M. Strimas-Mackey, M. Iliff, K. V. Rosenberg, ... S. Kelling (2019). Comparing abundance distributions and range maps in spatial conservation planning for migratory species. Ecological Applications. https://doi.org/10.1002/eap.2058.

Daniel Fink, Tom Auer, Alison Johnston, Viviana Ruiz-Gutierrez, Wesley M. Hochachka, Steve Kelling (2019). Modeling avian full annual cycle distribution and population trends with citizen science data. Ecological Applications. https://doi.org/10.1002/eap.2056.

Marje Prank, Shawn C Kenaley, Gary C Bergstrom, Maricelis Acevedo, Natalie M Mahowald (2019). Climate change impacts the spread potential of wheat stem rust, a significant crop disease. Environmental Research Letters. https://doi.org/10.1088/1748-9326/ab57de.

Jonathan Kuck, Tri Dao, Hamid Rezatofighi, Ashish Sabharwal, Stefano Ermon (2019). Approximating the Permanent by Sampling from Adaptive Partitions. Advances in Neural Information Processing Systems 32. [pdf]

Sawyer Birnbaum, Volodymyr Kuleshov, Zayd Enam, Pang Wei W. Koh, Stefano Ermon (2019). Temporal FiLM: Capturing Long-Range Sequence Dependencies with Feature-Wise Modulations. Advances in Neural Information Processing Systems 32. [pdf]

Yang Song, Chenlin Meng, Stefano Ermon (2019). MintNet: Building Invertible Neural Networks with Masked Convolutions. Advances in Neural Information Processing Systems 32. [pdf]

Aditya Grover, Jiaming Song, Ashish Kapoor, Kenneth Tran, Alekh Agarwal, Eric J. Horvitz, Stefano Ermon (2019). Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting. Advances in Neural Information Processing Systems 32. [pdf]

Lantao Yu, Tianhe Yu, Chelsea Finn, Stefano Ermon (2019). Meta-Inverse Reinforcement Learning with Probabilistic Context Variables. Advances in Neural Information Processing Systems 32. [pdf]

Yang Song, Stefano Ermon (2019). Generative Modeling by Estimating Gradients of the Data Distribution. Advances in Neural Information Processing Systems 32. [pdf]

Nicole D. Sintov, Lee V. White, Hugh Walpole (2019). Thermostat wars? The roles of gender and thermal comfort negotiations in household energy use behavior. PLOS ONE. https://doi.org/10.1371/journal.pone.0224198.

David Rolnick, Priya L. Donti, Lynn H. Kaack, Kelly Kochanski, Alexandre Lacoste, Kris Sankaran, ... Yoshua Bengio (2019). Tackling Climate Change with Machine Learning. arXiv: 1906.05433. [pdf]

Amrita Gupta, Bistra Dilkina (2019). Budget-Constrained Demand-Weighted Network Design for Resilient Infrastructure. 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI). https://doi.org/10.1109/ICTAI.2019.00070.

Xinrun Wang, Milind Tambe, Branislav Bošanský, Bo An (2019). When Players Affect Target Values: Modeling and Solving Dynamic Partially Observable Security Games. GameSec 2019: Decision and Game Theory for Security. https://doi.org/10.1007/978-3-030-32430-8_32.

Daniel Freund, Shane G. Henderson, Eoin O'Mahony, David B. Shmoys (2019). Analytics and Bikes: Riding Tandem with Motivate to Improve Mobility. INFORMS Journal on Applied Analytics. https://doi.org/10.1287/inte.2019.1005.

Rafael M. Almeida, Qinru Shi, Jonathan M. Gomes-Selman, Xiaojian Wu, Yexiang Xue, Hector Angarita, ... Alexander S. Flecker (2019). Reducing greenhouse gas emissions of Amazon hydropower with strategic dam planning. Nature Communications. https://doi.org/10.1038/s41467-019-12179-5.

Douglas S. Hamilton, Rachel A. Scanza, Yan Feng, Joseph Guinness, Jasper F. Kok, Longlei Li, ... Natalie M. Mahowald (2019). Improved methodologies for Earth system modelling of atmospheric soluble iron and observation comparisons using the Mechanism of Intermediate complexity for Modelling Iron (MIMI v1.0). Geoscientific Model Development. https://doi.org/10.5194/gmd-12-3835-2019. [pdf]

Carla Gomes, Thomas Dietterich, Christopher Barrett, Jon Conrad, Bistra Dilkina, Stefano Ermon, ... Mary Lou Zeeman (2019). Computational Sustainability: Computing for a Better World and a Sustainable Future. Communications of the ACM. https://doi.org/10.1145/3339399. [pdf]

Burak Uzkent, Evan Sheehan, Chenlin Meng, Zhongyi Tang, Marshall Burke, David Lobell, Stefano Ermon (2019). Learning to Interpret Satellite Images using Wikipedia. Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence. https://doi.org/10.24963/ijcai.2019/502. [pdf]

Evan Sheehan, Chenlin Meng, Matthew Tan, Burak Uzkent, Neal Jean, Marshall Burke, ... Stefano Ermon (2019). Predicting Economic Development using Geolocated Wikipedia Articles. Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining - KDD '19. https://doi.org/10.1145/3292500.3330784.

David Hathcock, Steven H. Strogatz (2019). Fitness dependence of the fixation-time distribution for evolutionary dynamics on graphs. Physical Review E. https://doi.org/10.1103/PhysRevE.100.012408.

Yang Song, Sahaj Garg, Jiaxin Shi, Stefano Ermon (2019). Sliced Score Matching: A Scalable Approach to Density and Score Estimation. Conference on Uncertainty in Artificial Intelligence (UAI2019). [pdf]

Jonathan Kuck, Tri Dao, Shenjia Zhao, Burak Bartan, Ashish Sabharwal, Stefano Ermon (2019). Adaptive Hashing for Model Counting. Conference on Uncertainty in Artificial Intelligence (UAI2019). [pdf]

Sebastian E. Ament, Helge S. Stein, Dan Guevarra, Lan Zhou, Joel A. Haber, David A. Boyd, ... Carla P. Gomes (2019). Multi-component background learning automates signal detection for spectroscopic data. npj Computational Materials. https://doi.org/10.1038/s41524-019-0213-0.

Shengjia Zhao, Jiaming Song, Stefano Ermon (2019). InfoVAE: Balancing Learning and Inference in Variational Autoencoders. Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence. https://doi.org/10.1609/aaai.v33i01.33015885. [pdf]

Neal Jean, Sherrie Wang, Anshul Samar, George Azzari, David Lobell, Stefano Ermon (2019). Tile2Vec: Unsupervised Representation Learning for Spatially Distributed Data. Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence. https://doi.org/10.1609/aaai.v33i01.33013967. [pdf]

Di Chen, Carla P. Gomes (2019). Bias Reduction via End-to-End Shift Learning: Application to Citizen Science. Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence. https://doi.org/10.1609/aaai.v33i01.3301493. [pdf]

Johan Bjorck, Brendan H. Rappazzo, Di Chen, Richard Bernstein, Peter H. Wrege, Carla P. Gomes (2019). Automatic Detection and Compression for Passive Acoustic Monitoring of the African Forest Elephant. Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence. https://doi.org/10.1609/aaai.v33i01.3301476. [pdf]

Carla P. Gomes, Bart Selman, John M. Gregoire (2019). Artificial intelligence for materials discovery. MRS Bulletin. https://doi.org/10.1557/mrs.2019.158.

P. van den Driessche, Abdul-Aziz Yakubu (2019). Age structured discrete-time disease models with demographic population cycles. Journal of Biological Dynamics. https://doi.org/10.1080/17513758.2020.1743885.

Anmol Kabra, Yexiang Xue, Carla P. Gomes (2019). CPU-accelerated principal-agent game for scalable citizen science. Proceedings of the Conference on Computing & Sustainable Societies - COMPASS '19. https://doi.org/10.1145/3314344.3332495.

Tadesse Zemicheal, Thomas G. Dietterich (2019). Anomaly detection in the presence of missing values for weather data quality control. Proceedings of the Conference on Computing & Sustainable Societies - COMPASS '19. https://doi.org/10.1145/3314344.3332490.

Douglas H. Fisher, Emily Markert, Abigail Roberts, Kamala Varma (2019). Region Radio: An AI that Finds and Tells Stories about Places. Tenth International Conference on Computational Creativity (ICCC 2019). [pdf]

Douglas H. Fisher, Haerin Shin (2019). Critique as Creativity: Towards Developing Computational Commentators on Creative Works. Tenth International Conference on Computational Creativity (ICCC 2019). [pdf]

Amrita Gupta, Bistra Dilkina, Dana J. Morin, Angela K. Fuller, J. Andrew Royle, Christopher Sutherland, Carla P. Gomes (2019). Reserve design to optimize functional connectivity and animal density. Conservation Biology. https://doi.org/10.1111/cobi.13369.

Warren B. Powell (2019). A unified framework for stochastic optimization. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2018.07.014.

Caleb Robinson, Le Hou, Kolya Malkin, Rachel Soobitsky, Jacob Czawlytko, Bistra Dilkina, Nebojsa Jojic (2019). Large Scale High-Resolution Land Cover Mapping With Multi-Resolution Data. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). [pdf]

Rose M Rustowicz, Robin Cheong, Lijing Wang, Stefano Ermon, Marshall Burke, David Lobell (2019). Semantic Segmentation of Crop Type in Africa: A Novel Dataset and Analysis of Deep Learning Methods. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. [pdf]

Kristy Choi, Kedar Tatwawadi, Aditya Grover, Tsachy Weissman, Stefano Ermon (2019). Neural Joint Source-Channel Coding. Proceedings of the 36th International Conference on Machine Learning.

Aditya Grover, Aaron Zweig, Stefano Ermon (2019). Graphite: Iterative Generative Modeling of Graphs. Proceedings of the 36th International Conference on Machine Learning.

Ali Malik, Volodymyr Kuleshov, Jiaming Song, Danny Nemer, Harlan Seymour, Stefano Ermon (2019). Calibrated Model-Based Deep Reinforcement Learning. Proceedings of the 36th International Conference on Machine Learning.

Hongyu Ren, Shengjia Zhao, Stefano Ermon (2019). Adaptive Antithetic Sampling for Variance Reduction. Proceedings of the 36th International Conference on Machine Learning.

Lantao Yu, Jiaming Song, Stefano Ermon (2019). Multi-Agent Adversarial Inverse Reinforcement Learning. Proceedings of the 36th International Conference on Machine Learning.

Kevin P. O'Keeffe, Amin Anjomshoaa, Steven H. Strogatz, Paolo Santi, Carlo Ratti (2019). Quantifying the sensing power of vehicle fleets. Proceedings of the National Academy of Sciences (PNAS). https://doi.org/10.1073/pnas.1821667116.

Po-Wei Wang, Priya Donti, Bryan Wilder, Zico Kolter (2019). SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver. Proceedings of the 36th International Conference on Machine Learning, PMLR. [pdf]

Shahrzad Gholami, Amulya Yadav, Long Tran-Thanh, Bistra Dilkina, Milind Tambe (2019). Don't Put All Your Strategies in One Basket: Playing Green Security Games with Imperfect Prior Knowledge. Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems.

Elizabeth Bondi, Hoon Oh, Haifeng Xu, Fei Fang, Bistra Dilkina, Milind Tambe (2019). Broken Signals in Security Games: Coordinating Patrollers and Sensors in the Real World. Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems.

Elizabeth Bondi, Hoon Oh, Haifeng Xu, Fei Fang, Bistra Dilkina, Milind Tambe (2019). Using Game Theory in Real Time in the Real World: A Conservation Case Study. Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems.

Julia Berazneva, Jon M Conrad, David T Güereña, Johannes Lehmann, Dominic Woolf (2019). Agricultural Productivity and Soil Carbon Dynamics: A Bioeconomic Model. American Journal of Agricultural Economics. https://doi.org/10.1093/ajae/aaz014.

Junwen Bai, Zihang Lai, Runzhe Yang, Yexiang Xue, John Gregoire, Carla Gomes (2019). Imitation Refinement for X-ray Diffraction Signal Processing. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). https://doi.org/10.1109/ICASSP.2019.8683723.

Christopher J Lauer, Claire A Montgomery, Thomas G Dietterich (2019). Managing Fragmented Fire-Threatened Landscapes with Spatial Externalities. Forest Science. https://doi.org/10.1093/forsci/fxz012.

Aditya Grover, Eric Wang, Aaron Zweig, Stefano Ermon (2019). Stochastic Optimization of Sorting Networks via Continuous Relaxations. Seventh International Conference on Learning Representations (ICLR 2019). [pdf]

J. Nicolas Hernandez-Aguilera, Jon M. Conrad, Miguel I. Gómez, Amanda D. Rodewald (2019). The Economics and Ecology of Shade-grown Coffee: A Model to Incentivize Shade and Bird Conservation. Ecological Economics. https://doi.org/10.1016/j.ecolecon.2019.01.015.

Carla P. Gomes, Junwen Bai, Yexiang Xue, Johan Björck, Brendan Rappazzo, Sebastian Ament, ... John M. Gregoire (2019). CRYSTAL: a multi-agent AI system for automated mapping of materials' crystal structures. MRS Communications. https://doi.org/10.1557/mrc.2019.50.

Rui Shu, Hung Bui, Jay Whang, Stefano Ermon (2019). Training Variational Autoencoders with Buffered Stochastic Variational Inference. Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS).

Jiaming Song, Pratyusha Kalluri, Aditya Grover, Shengjia Zhao, Stefano Ermon (2019). Learning Controllable Fair Representations. Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS).

Aditya Grover, Stefano Ermon (2019). Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization. Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS).

Mike Wu, Noah Goodman, Stefano Ermon (2019). Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference. Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS).

Sagar Jha, Jonathan Behrens, Theo Gkountouvas, Matthew Milano, Weijia Song, Edward Tremel, ... Kenneth P. Birman (2019). Derecho: Fast State Machine Replication for Cloud Services. ACM Transactions on Computer Systems (TOCS). https://doi.org/10.1145/3302258.

Richard Schuster, Scott Wilson, Amanda D. Rodewald, Peter Arcese, Daniel Fink, Tom Auer, Joseph. R. Bennett (2019). Optimizing the conservation of migratory species over their full annual cycle. Nature Communications. https://doi.org/10.1038/s41467-019-09723-8.

Jason Z. Kim, Zhixin Lu, Steven H. Strogatz, Danielle S. Bassett (2019). Conformational control of mechanical networks. Nature Physics. https://doi.org/10.1038/s41567-019-0475-y.

Fei Fang, Milind Tambe, Bistra Dilkina, Andrew J. Plumptre (2019). Artificial Intelligence and Conservation. https://doi.org/10.1017/9781108587792.

Frank A. La Sorte, Daniel Fink, Alison Johnston (2019). Time of emergence of novel climates for North American migratory bird populations. Ecography. https://doi.org/10.1111/ecog.04408.

Saksham Agarwal, Shijin Rajakrishnan, Akshay Narayan, Rachit Agarwal, David Shmoys, Amin Vahdat (2018). Sincronia: near-optimal network design for coflows. Proceedings of the 2018 Conference of the ACM Special Interest Group on Data Communication (SIGCOMM '18). https://doi.org/10.1145/3230543.3230569.

Barak Oshri, Annie Hu, Peter Adelson, Xiao Chen, Pascaline Dupas, Jeremy Weinstein, ... Stefano Ermon (2018). Infrastructure Quality Assessment in Africa using Satellite Imagery and Deep Learning. Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD '18). https://doi.org/10.1145/3219819.3219924.

Patrick R. Steele, Shane G. Henderson, David B. Shmoys (2018). Aggregating courier deliveries. Naval Research Logistics (NRL). https://doi.org/10.1002/nav.21804.

Stephan Eismann, Daniel Levy, Rui Shu, Stefan Bartzsch, Stefano Ermon (2018). Bayesian optimization and attribute adjustment. Proc. 34th Conference on Uncertainty in Artificial Intelligence (UAI-18) [pdf]

Shengjia Zhao, Jiaming Song, Stefano Ermon (2018). A Lagrangian Perspective on Latent Variable Generative Models. Proc. 34th Conference on Uncertainty in Artificial Intelligence (UAI-18) [pdf]

Travis Moore, Weng-Keen Wong (2018). An Efficient Quantile Spatial Scan Statistic for Finding Unusual Regions in Continuous Spatial Data with Covariates. Proc. 34th Conference on Uncertainty in Artificial Intelligence (UAI-18) [pdf]

Hongyu Ren, Russell Stewart, Jiaming Song, Volodymyr Kuleshov, Stefano Ermon (2018). Adversarial Constraint Learning for Structured Prediction. Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence. https://doi.org/10.24963/ijcai.2018/366. [pdf]

Amrita Gupta, Mehrdad Farajtabar, Bistra Dilkina, Hongyuan Zha (2018). Discrete Interventions in Hawkes Processes with Applications in Invasive Species Management. Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence. https://doi.org/10.24963/ijcai.2018/470. [pdf]

Elizabeth Bondi, Ashish Kapoor, Debadeepta Dey, James Piavis, Shital Shah, Robert Hannaford, ... Milind Tambe (2018). Near Real-Time Detection of Poachers from Drones in AirSim. Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence. https://doi.org/10.24963/ijcai.2018/847. [pdf]

Daniel Sheldon, Kevin Winner, Debora Sujono (2018). Learning in Integer Latent Variable Models with Nested Automatic Differentiation. Proceedings of the 35th International Conference on Machine Learning (PMLR).

Di Chen, Yexiang Xue, Carla Gomes (2018). End-to-End Learning for the Deep Multivariate Probit Model. Proceedings of the 35th International Conference on Machine Learning (PMLR).

Yang Song, Jiaming Song, Stefano Ermon (2018). Accelerating Natural Gradient with Higher-Order Invariance. Proceedings of the 35th International Conference on Machine Learning (PMLR).

Manik Dhar, Aditya Grover, Stefano Ermon (2018). Modeling Sparse Deviations for Compressed Sensing using Generative Models. Proceedings of the 35th International Conference on Machine Learning (PMLR).

Volodymyr Kuleshov, Nathan Fenner, Stefano Ermon (2018). Accurate Uncertainties for Deep Learning Using Calibrated Regression. Proceedings of the 35th International Conference on Machine Learning (PMLR).

Bryan Wilder, Han Ching Ou, Kayla de la Haye, Milind Tambe (2018). Optimizing Network Structure for Preventative Health. Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems.

Shahrzad Gholami, Sara Mc Carthy, Bistra Dilkina, Andrew Plumptre, Milind Tambe, Margaret Driciru, ... Eric Enyel (2018). Adversary Models Account for Imperfect Crime Data: Forecasting and Planning against Real-world Poachers. Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems.

Natalie M. Mahowald, Douglas S. Hamilton, Katherine R. M. Mackey, J. Keith Moore, Alex R. Baker, Rachel A. Scanza, Yan Zhang (2018). Aerosol trace metal leaching and impacts on marine microorganisms. Nature Communications. https://doi.org/10.1038/s41467-018-04970-7.

Nicole, Sintov, Viviane Seyranian, Milind Tambe (2018). Adoption of Conservation Technologies. Wildlife Crime: From Theory to Practice.

Jonathan M. Gomes-Selman, Qinru Shi, Yexiang Xue, Roosevelt García-Villacorta, Alexander S. Flecker, Carla P. Gomes (2018). Boosting Efficiency for Computing the Pareto Frontier on Tree Structured Networks. CPAIOR 2018: Integration of Constraint Programming, Artificial Intelligence, and Operations Research. https://doi.org/10.1007/978-3-319-93031-2_19.

Junwen Bai, Sebastian Ament, Guillaume Perez, John Gregoire, Carla Gomes (2018). An Efficient Relaxed Projection Method for Constrained Non-negative Matrix Factorization with Application to the Phase-Mapping Problem in Materials Science. CPAIOR 2018: Integration of Constraint Programming, Artificial Intelligence, and Operations Research. https://doi.org/10.1007/978-3-319-93031-2_4.

Huaiyang Zhong, Xiaocheng Li, David Lobell, Stefano Ermon, Margaret L. Brandeau (2018). Hierarchical modeling of seed variety yields and decision making for future planting plans. Environment Systems and Decisions. https://doi.org/10.1007/s10669-018-9695-4.

Hangil Chung, Daniel Freund, David B. Shmoys (2018). Bike Angels: An Analysis of Citi Bike's Incentive Program. Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies (COMPASS '18). https://doi.org/10.1145/3209811.3209866. [pdf]

Qinru Shi, Jonathan M. Gomes-Selman, Roosevelt García-Villacorta, Suresh Sethi, Alexander S. Flecker, Carla P. Gomes (2018). Efficiently Optimizing for Dendritic Connectivity on Tree-Structured Networks in a Multi-Objective Framework. Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies (COMPASS '18). https://doi.org/10.1145/3209811.3209878. [pdf]

Amrita Gupta, Caleb Robinson, Bistra Dilkina (2018). Infrastructure Resilience for Climate Adaptation. Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies (COMPASS '18). https://doi.org/10.1145/3209811.3209859. [pdf]

Caleb Robinson, Bistra Dilkina (2018). A Machine Learning Approach to Modeling Human Migration. Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies (COMPASS '18). https://doi.org/10.1145/3209811.3209868. [pdf]

Srinivasan Iyengar, Stephen Lee, Daniel Sheldon, Prashant Shenoy (2018). SolarClique: Detecting Anomalies in Residential Solar Arrays. Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies (COMPASS '18). https://doi.org/10.1145/3209811.3209860. [pdf]

Elizabeth Bondi, Lucas Joppa, Milind Tambe, Debadeepta Dey, Ashish Kapoor, Jim Piavis, ... Arvind Iyer (2018). AirSim-W: A Simulation Environment for Wildlife Conservation with UAVs. Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies (COMPASS '18). https://doi.org/10.1145/3209811.3209880. [pdf]

Anna X. Wang, Caelin Tran, Nikhil Desai, David Lobell, Stefano Ermon (2018). Deep Transfer Learning for Crop Yield Prediction with Remote Sensing Data. Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies (COMPASS '18). https://doi.org/10.1145/3209811.3212707. [pdf]

Kim Meyer Hall, Heidi J. Albers, Majid Alkaee Taleghan, Thomas G. Dietterich (2018). Optimal Spatial-Dynamic Management of Stochastic Species Invasions. Environmental and Resource Economics. https://doi.org/10.1007/s10640-017-0127-6.

Frank A. La Sorte, Daniel Fink, Alison Johnston (2018). Seasonal associations with novel climates for North American migratory bird populations. Ecology Letters. https://doi.org/10.1111/ele.12951.

C. H. Fleming, D. Sheldon, W. F. Fagan, P. Leimgruber, T. Mueller, D. Nandintsetseg, ... J. M. Calabrese (2018). Correcting for missing and irregular data in home-range estimation. Ecological Applications. https://doi.org/10.1002/eap.1704.

C. Ponce, D. S. Bindel, P. S. Vassilevski (2018). A Nonlinear Algebraic Multigrid Framework for the Power Flow Equations. SIAM Journal on Scientific Computing. https://doi.org/10.1137/16M1109965.

M. M. Vazifeh, P. Santi, G. Resta, S. H. Strogatz, C. Ratti (2018). Addressing the minimum fleet problem in on-demand urban mobility. Nature. https://doi.org/10.1038/s41586-018-0095-1.

Mary Lou Zeeman, Katherine Meyer, Erika Bussmann, Alanna Hoyer-Leitzel, Sarah Iams, Ian J. Klasky, ... Stephen Ligtenberg (2018). Resilience of socially valued properties of natural systems to repeated disturbance: A framework to support value-laden management decisions. Natural Resource Modeling. https://doi.org/10.1111/nrm.12170.

Kevin Winner, Michael J. Noonan, Christen H. Fleming, Kirk A. Olson, Thomas Mueller, Daniel Sheldon, Justin M. Calabrese (2018). Statistical inference for home range overlap. Methods in Ecology and Evolution. https://doi.org/10.1111/2041-210X.13027.

Kyle G. Horton, Benjamin M. Van Doren, Frank A. La Sorte, Daniel Fink, Daniel Sheldon, Andrew Farnsworth, Jeffrey F. Kelly (2018). Navigating north: how body mass and winds shape avian flight behaviours across a North American migratory flyway. Ecology Letters. https://doi.org/10.1111/ele.12971.

Joseph Durante, Raj Patel, Warren B. Powell (2018). Scenario Generation Methods that Replicate Crossing Times in Spatially Distributed Stochastic Systems. SIAM/ASA Journal on Uncertainty Quantification. https://doi.org/10.1137/17M1120555.

Bolong Cheng, Warren B. Powell (2018). Co-Optimizing Battery Storage for the Frequency Regulation and Energy Arbitrage Using Multi-Scale Dynamic Programming. IEEE Transactions on Smart Grid. https://doi.org/10.1109/TSG.2016.2605141.

Javad Khazaei, Warren B. Powell (2018). SMART-Invest: a stochastic, dynamic planning for optimizing investments in wind, solar, and storage in the presence of fossil fuels. The case of the PJM electricity market. Energy Systems. https://doi.org/10.1007/s12667-016-0226-4.

P. van den Driessche, Abdul-Aziz Yakubu (2018). Disease Extinction Versus Persistence in Discrete-Time Epidemic Models. Bulletin of Mathematical Biology. https://doi.org/10.1007/s11538-018-0426-2.

Aditya Grover, Ramki Gummadi, Miguel Lazaro-Gredilla, Dale Schuurmans, Stefano Ermon (2018). Variational Rejection Sampling. Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics (PMLR). [pdf]

Aditya Grover, Todor Markov, Peter Attia, Norman Jin, Nicolas Perkins, Bryan Cheong, ... Stefano Ermon (2018). Best arm identification in multi-armed bandits with delayed feedback. Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics (PMLR). [pdf]

Jon M. Conrad, Linda Nøstbakken (2018). Innovation and site quality: Implications for the timing of investments in renewable energy. Energy. https://doi.org/10.1016/j.energy.2018.01.166.

Orin J. Robinson, Viviana Ruiz-Gutierrez, Daniel Fink (2018). Correcting for bias in distribution modelling for rare species using citizen science data. Diversity and Distributions. https://doi.org/10.1111/ddi.12698.

Soroush Alamdari, David Shmoys (2018). A Bicriteria Approximation Algorithm for the k-Center and k-Median Problems. Approximation and Online Algorithms (WAOA 2017). https://doi.org/10.1007/978-3-319-89441-6_6.

Yingfei Wang, Warren B. Powell (2018). Finite-Time Analysis for the Knowledge-Gradient Policy. SIAM Journal on Control and Optimization. https://doi.org/10.1137/16M1073388.

Majid Alkaee Taleghan, Thomas G. Dietterich (2018). Efficient Exploration for Constrained MDPs. 2018 AAAI Spring Symposium Series. [pdf]

Junwen Bai, Yexiang Xue, Johan Bjorck, Ronan Le Bras, Brendan Rappazzo, Richard Bernstein, ... Carla P. Gomes (2018). Phase Mapper: Accelerating Materials Discovery with AI. AI Magazine. https://doi.org/10.1609/aimag.v39i1.2785.

Hongyu Ren, Russell Stewart, Jiaming Song, Volodymyr Kuleshov, Stefano Ermon (2018). Learning with Weak Supervision from Physics and Data-Driven Constraints. AI Magazine. https://doi.org/10.1609/aimag.v39i1.2776.

Tsvetan Asamov, Warren B. Powell (2018). Regularized Decomposition of High-Dimensional Multistage Stochastic Programs with Markov Uncertainty. SIAM Journal on Optimization. https://doi.org/10.1137/16M1072231.

Douglas H. Fisher, Jacqueline Cameron, Tamara L. Clegg, Stephanie E. August (2018). Integrating Social Good into CS Education. Proceedings of the 49th ACM Technical Symposium on Computer Science Education (SIGCSE '18). https://doi.org/10.1145/3159450.3159622. [pdf]

Elizabeth Bondi, Fei Fang, Mark Hamilton, Debarun Kar, Donnabell Dmello, Jongmoo Choi, ... Ram Nevatia (2018). SPOT Poachers in Action: Augmenting Conservation Drones With Automatic Detection in Near Real Time. The Thirtieth AAAI Conference on Innovative Applications of Artificial Intelligence (IAAI-18).

Johan Bjorck, Yiwei Bai, Xiaojian Wu, Yexiang Xue, Mark Whitmore, Carla Gomes (2018). Scalable Relaxations of Sparse Packing Constraints: Optimal Biocontrol in Predator-Prey Networks. Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18). [pdf]

Bryan Wilder, Sze-Chuan Suen, Milind Tambe (2018). Preventing Infectious Disease in Dynamic Populations Under Uncertainty. Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18). [pdf]

Luming Tang, Yexiang Xue, Di Chen, Carla P. Gomes (2018). Multi-Entity Dependence Learning With Rich Context via Conditional Variational Auto-Encoder. Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18). [pdf]

Aditya Grover, Manik Dhar, Stefano Ermon (2018). Flow-GAN: Combining Maximum Likelihood and Adversarial Learning in Generative Models. Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18). [pdf]

Xiaojian Wu, Jonathan Gomes-Selman, Qinru Shi, Yexiang Xue, Roosevelt Garcia-Villacorta, Elizabeth Anderson, ... Carla Gomes (2018). Efficiently Approximating the Pareto Frontier: Hydropower Dam Placement in the Amazon Basin. Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18). [pdf]

Daniel Levy, Stefano Ermon (2018). Deterministic Policy Optimization by Combining Pathwise and Score Function Estimators for Discrete Action Spaces. Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18). [pdf]

Aditya Grover, Stefano Ermon (2018). Boosted Generative Models. Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18). [pdf]

Jonathan Kuck, Ashish Sabharwal, Stefano Ermon (2018). Approximate Inference via Weighted Rademacher Complexity. Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18). [pdf]

Shahrzad Gholami, Benjamin Ford, Debarun Kar, Fei Fang, Milind Tambe, Andrew Plumptre, ... Joshua Mabonga (2018). Evaluation of Predictive Models for Wildlife Poaching Activity through Controlled Field Test in Uganda. Workshops at the Thirty-Second AAAI Conference on Artificial Intelligence: Engineering Dependable and Secure Machine Learning Systems.

Bryan Wilder, Sze-Chuan Suen, Milind Tambe (2018). Preventing Infectious Disease in Dynamic Populations under Uncertainty. Workshops at the Thirty-Second AAAI Conference on Artificial Intelligence: Health Intelligence.

J. F. Ruiz-Muñoz, Zeyu You, Raviv Raich, Xiaoli Z. Fern (2018). Dictionary Learning for Bioacoustics Monitoring with Applications to Species Classification. Journal of Signal Processing Systems. https://doi.org/10.1007/s11265-016-1155-0.

Jon M. Conrad (2018). Real Options for Endangered Species. Ecological Economics. https://doi.org/10.1016/j.ecolecon.2017.07.027.

Joleah B. Lamb, Bette L. Willis, Evan A. Fiorenza, Courtney S. Couch, Robert Howard, Douglas N. Rader, ... C. Drew Harvell (2018). Plastic waste associated with disease on coral reefs. Science. https://doi.org/10.1126/science.aar3320.

Maureen A. O'Leary, Kenzley Alphonse, Arce H. Mariangeles, Dario Cavaliere, Andrea Cirranello, Thomas G. Dietterich, ... Marymegan Daly (2018). Crowds Replicate Performance of Scientific Experts Scoring Phylogenetic Matrices of Phenotypes. Systematic Biology. https://doi.org/10.1093/sysbio/syx052.

Bertrand Ottino-Loffler, Jacob G Scott, Steven H Strogatz (2017). Evolutionary dynamics of incubation periods. eLife. https://doi.org/10.7554/eLife.30212. [pdf]

Caleb Robinson, Bistra Dilkina, Jeffrey Hubbs, Wenwen Zhang, Subhrajit Guhathakurta, Marilyn A. Brown, Ram M. Pendyala (2017). Machine learning approaches for estimating commercial building energy consumption. Applied Energy. https://doi.org/10.1016/j.apenergy.2017.09.060.

Carla Gomes (2017). Keynotes: Computational sustainability. 2017 Sustainable Internet and ICT for Sustainability (SustainIT). https://doi.org/10.23919/SustainIT.2017.8379790.

Priya Donti, Brandon Amos, J. Zico Kolter (2017). Task-based End-to-end Model Learning in Stochastic Optimization. Advances in Neural Information Processing Systems 30 (NIPS 2017). [pdf]

Haifeng Xu, Benjamin Ford, Fei Fang, Bistra Dilkina, Andrew Plumptre, Milind Tambe, ... Joshua Mabonga (2017). Optimal Patrol Planning for Green Security Games with Black-Box Attackers. International Conference on Decision and Game Theory for Security. https://doi.org/10.1007/978-3-319-68711-7_24. [pdf]

Christopher J. Lauer, Claire A.Montgomery, Thomas G.Dietterich (2017). Spatial interactions and optimal forest management on a fire-threatened landscape. Forest Policy and Economics. https://doi.org/10.1016/j.forpol.2017.07.006.

Shahrzad Gholami, Benjamin Ford, Fei Fang, Andrew Plumptre, Milind Tambe, Margaret Driciru, ... Joshua Mabonga (2017). Taking it for a test drive: A hybrid spatio-temporal model for wildlife poaching prediction evaluated through a controlled field test. Proceedings of the European Conference on Machine Learning & Principles and Practice of Knowledge Discovery in Databases. [pdf]

Natalie M Mahowald, Daniel S Ward, Scott C Doney, Peter G Hess, James T Randerson (2017). Are the impacts of land use on warming underestimated in climate policy?. Environmental Research Letters. https://doi.org/10.1088/1748-9326/aa836d. [pdf]

Alice Paul, Daniel Freund, Aaron Ferber, David B. Shmoys, David P. Williamson (2017). Prize-Collecting TSP with a Budget Constraint. 25th Annual European Symposium on Algorithms (ESA 2017). https://doi.org/10.4230/LIPIcs.ESA.2017.62. [pdf]

Venu M. Garikapati, Daehyun You, Wenwen Zhang, Ram M. Pendyala, Subhrajit Guhathakurta, Marilyn A. Brown, Bistra Dilkina (2017). Estimating Household Travel Energy Consumption in Conjunction with a Travel Demand Forecasting Model. Transportation Research Record: Journal of the Transportation Research Board. https://doi.org/10.3141/2668-01.

Di Chen, Yexiang Xue, Daniel Fink, Shuo Chen, Carla P. Gomes (2017). Deep Multi-species Embedding. Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17). https://doi.org/10.24963/ijcai.2017/509. [pdf]

Xiaojian Wu, Yexiang Xue, Bart Selman, Carla P. Gomes (2017). XOR-Sampling for Network Design with Correlated Stochastic Events. Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17). https://doi.org/10.24963/ijcai.2017/647. arXiv: 1705.08218. [pdf]

Mark D. Reynolds, Brian L. Sullivan, Eric Hallstein, Sandra Matsumoto, Steve Kelling, Matthew Merrifield, ... Scott A. Morrison (2017). Dynamic conservation for migratory species. Science Advances. https://doi.org/10.1126/sciadv.1700707.

Neal Jean, Chi-Sing Ho, Amr Saleh, Niaz Banaei, Jennifer Dionne, Stefano Ermon (2017). Enabling rapid screening of bacterial blood infections with machine learning. ICML 2017 Workshop on Computational Biology.

Poster Presentation Award

Kevin Winner, Debora Sujono, Dan Sheldon (2017). Exact Inference for Integer Latent-Variable Models. Proceedings of the 34th International Conference on Machine Learning (PMLR). [pdf]

North American Bird Conservation Initiative, U.S. Committee (2017). The State of the Birds 2017: A Farm Bill Special Report.

Nathaniel D. Jensen, Russell Dean Toth, Yexiang Xue, Rich Bernstein, Eddy K. Chebelyon, Andrew G. Mude, ... Carla Gomes (2017). Don't Follow the Crowd: Incentives for Directed Spatial Sampling. Agricultural & Applied Economics Association (AAEA).

Alison Johnston, Daniel Fink, Wesley M. Hochachka, Steve Kelling (2017). Estimates of observer expertise improve species distributions from citizen science data. Methods in Ecology and Evolution. https://doi.org/10.1111/2041-210X.12838.

Frank A. La Sorte, Daniel Fink, Peter J. Blancher, Amanda D. Rodewald, Viviana Ruiz-Gutierrez, Kenneth V. Rosenberg, ... Steve Kelling (2017). Global change and the distributional dynamics of migratory bird populations wintering in Central America. Global Change Biology. https://doi.org/10.1111/gcb.13794.

Reid Pryzant, Stefano Ermon, David Lobell (2017). Monitoring Ethiopian Wheat Fungus with Satellite Imagery and Deep Feature Learning. CVPR 2017 EARTHVISION Workshop. https://doi.org/10.1109/CVPRW.2017.196. [pdf]

Best Presentation Award

Bertrand Ottino-Löffler, Jacob G. Scott, Steven H. Strogatz (2017). Takeover times for a simple model of network infection. Physical Review E. https://doi.org/10.1103/PhysRevE.96.012313.

Frank A. La Sorte, Daniel Fink, Jeffrey J. Buler, Andrew Farnsworth, Sergio A. Cabrera-Cruz (2017). Seasonal associations with urban light pollution for nocturnally migrating bird populations. Global Change Biology. https://doi.org/10.1111/gcb.13792.

Christen H. Fleming, Daniel Sheldon, Eliezer Gurarie, William F. Fagan, Scott LaPoint, Justin M. Calabrese (2017). Kálmán filters for continuous-time movement models. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2017.04.008.

Santiago Molina, Angela K. Fuller, Dana J. Morin, J. Andrew Royle (2017). Use of spatial capture-recapture to estimate density of Andean bears in northern Ecuador. Ursus. https://doi.org/10.2192/URSU-D-16-00030.1.

Daniel Freund, Shane G. Henderson, David B. Shmoys (2017). Minimizing Multimodular Functions and Allocating Capacity in Bike-Sharing Systems. Integer Programming and Combinatorial Optimization (IPCO 2017). https://doi.org/10.1007/978-3-319-59250-3_16.

Siddhartha Banerjee, Daniel Freund, Thodoris Lykouris (2017). Pricing and Optimization in Shared Vehicle Systems: An Approximation Framework. Proceedings of the 2017 ACM Conference on Economics and Computation (EC '17). https://doi.org/10.1145/3033274.3085099. arXiv: 1608.06819. [pdf]

Junwen Bai, Johan Bjorck, Yexiang Xue, Santosh K. Suram, John Gregoire, Carla Gomes (2017). Relaxation Methods for Constrained Matrix Factorization Problems: Solving the Phase Mapping Problem in Materials Discovery. Fourteenth International Conference on Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming (CPAIOR). https://doi.org/10.1007/978-3-319-59776-8_9.

Mateo Diaz, Ronan Le Bras, Carla Gomes (2017). In Search of Balance: The Challenge of Generating Balanced Latin Rectangles. Fourteenth International Conference on Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming (CPAIOR). https://doi.org/10.1007/978-3-319-59776-8_6.

Nicole Sintov, Debarun Kar, Thanh Nguyen, Fei Fang, Kevin Hoffman, Arnaud Lyet, Milind Tambe (2017). Keeping it Real: Using Real-World Problems to Teach AI to Diverse Audiences. AI Magazine. https://doi.org/10.1609/aimag.v38i2.2733. [pdf]

Tianshu Liu, Nichole Nadermann, Zhenping He, Steven H. Strogatz, Chung-Yuen Hui, Anand Jagota (2017). Spontaneous Droplet Motion on a Periodically Compliant Substrate. Langmuir. https://doi.org/10.1021/acs.langmuir.7b01414.

Debarun Kar, Benjamin Ford, Shahrzad Gholami, Fei Fang, Andrew Plumptre, Milind Tambe, ... Aggrey Rwetsiba (2017). Cloudy with a Chance of Poaching: Adversary Behavior Modeling and Forecasting with Real-World Poaching Data. International Conference on Autonomous Agents and Multiagent Systems, AAMAS '17. [pdf]

Maurice Cheung, Julián Mestre, David B. Shmoys, José Verschae (2017). A Primal-Dual Approximation Algorithm for Min-Sum Single-Machine Scheduling Problems. SIAM Journal on Discrete Mathematics. https://doi.org/10.1137/16M1086819.

Nahid Jafari, Bryan L. Nuse, Clinton T. Moore, Bistra Dilkina, Jeffrey Hepinstall-Cymerman (2017). Achieving full connectivity of sites in the multiperiod reserve network design problem. Computers & Operations Research. https://doi.org/10.1016/j.cor.2016.12.017.

Moussa Doumbia, Abdul-Aziz Yakubu (2017). Malaria incidence and anopheles mosquito density in irrigated and adjacent non-irrigated villages of Niono in Mali. Discrete and Continuous Dynamical Systems - Series B (DCDS-B). https://doi.org/10.3934/dcdsb.2017042.

Fei Fang, Benjamin Ford, Rong Yang, Milind Tambe, Andrew M. Lemieux (2017). PAWS: Game-Theory Based Protection Assistant for Wildlife Security. Conservation Criminology, Ch. 10

Somayeh Moazeni, Warren B. Powell, Boris Defourny, Belgacem Bouzaiene-Ayari (2017). Parallel Nonstationary Direct Policy Search for Risk-Averse Stochastic Optimization. INFORMS Journal on Computing. https://doi.org/10.1287/ijoc.2016.0733.

C. L. Archer, H. P. Simão, W. Kempton, W. B. Powell, M. J. Dvorak (2017). The challenge of integrating offshore wind power in the U.S. electric grid. Part I: Wind forecast error. Renewable Energy. https://doi.org/10.1016/j.renene.2016.11.047.

H. P. Simão, W. B. Powell, C. L. Archer, W. Kempton (2017). The challenge of integrating offshore wind power in the U.S. electric grid. Part II: Simulation of electricity market operations. Renewable Energy. https://doi.org/10.1016/j.renene.2016.11.049.

Dana J. Morin (2017). Community engagement and training are keys to successful landscape-scale Andean bear camera-trap study. International Bear News. [pdf]

Douglas H. Fisher (2017). Establishing Conventions for Citing Educational Materials. Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE '17). https://doi.org/10.1145/3017680.3022396.

R. Tachet, O. Sagarra, P. Santi, G. Resta, M. Szell, S. H. Strogatz, C. Ratti (2017). Scaling Law of Urban Ride Sharing. Scientific Reports. https://doi.org/10.1038/srep42868. arXiv: 1610.09921. [pdf]

Taxi-sharing in cities follows universal maths law
Nature — Mar 6, 2017
Ride-sharing study findings are scalable to different cities
Cornell Chronicle — Mar 6, 2017
Sharing the fares
MIT News — Mar 6, 2017
City folk: You could probably share rides a lot more often than you do
Popular Science — Mar 7, 2017

Revathy Narasimhan, Xiaoli Z. Fern, Raviv Raich (2017). Simultaneous segmentation and classification of bird song using CNN. 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). https://doi.org/10.1109/ICASSP.2017.7952135.

Lina Al-Kanj, Belgacem Bouzaiene-Ayari, Warren B. Powell (2017). A Probability Model for Grid Faults Using Incomplete Information. IEEE Transactions on Smart Grid. https://doi.org/10.1109/TSG.2015.2447275.

Fei Fang, Thanh H. Nguyen, Rob Pickles, Wai Y. Lam, Gopalasamy R. Clements, Bo An, ... Andrew Lemieux (2017). PAWS - A Deployed Game-Theoretic Application to Combat Poaching. AI Magazine. https://doi.org/10.1609/aimag.v38i1.2710. [pdf]

Natalie M. Mahowald, Rachel Scanza, Janice Brahney, Christine L. Goodale, Peter G. Hess, J. Keith Moore, Jason Neff (2017). Aerosol Deposition Impacts on Land and Ocean Carbon Cycles. Current Climate Change Reports. https://doi.org/10.1007/s40641-017-0056-z. [pdf]

Joleah B. Lamb, Jeroen A. J. M. van de Water, David G. Bourne, Craig Altier, Margaux Y. Hein, Evan A. Fiorenza, ... C. Drew Harvell (2017). Seagrass ecosystems reduce exposure to bacterial pathogens of humans, fishes, and invertebrates. Science. https://doi.org/10.1126/science.aal1956.

Yexiang Xue, Junwen Bai, Ronan Le Bras, Brendan Rappazzo, Richard Bernstein, Johan Bjorck, ... Carla P. Gomes (2017). Phase-Mapper: An AI Platform to Accelerate High Throughput Materials Discovery. Twenty-Ninth IAAI Conference. [pdf]

Deployed Application Award

Yann Dujardin, Tom Dietterich, Iadine Chadès (2017). Three New Algorithms to Solve N-POMDPs. AAAI-17 Special Track on Computational Sustainability. [pdf]

Jiaxuan You, Xiaocheng Li, Melvin Low, David Lobell, Stefano Ermon (2017). Deep Gaussian Process for Crop Yield Prediction Based on Remote Sensing Data. AAAI-17 Special Track on Computational Sustainability. [pdf]

Best Student Paper - CompSust Track

Xiaojian Wu, Akshat Kumar, Daniel Sheldon, Shlomo Zilberstein (2017). Robust Optimization for Tree-Structured Stochastic Network Design. AAAI-17 Special Track on Computational Sustainability. arXiv: 1612.00104. [pdf]

Best Paper - CompSust Track

Yexiang Xue, Xiaojian Wu, Dana Morin, Bistra Dilkina, Angela Fuller, J. Andrew Royle, Carla Gomes (2017). Dynamic Optimization of Landscape Connectivity Embedding Spatial-Capture-Recapture Information. AAAI-17 Special Track on Computational Sustainability. [pdf]

Douglas H. Fisher (2017). A Selected Summary of AI for Computational Sustainability. AAAI-17 Senior Member Summary Talks.

Bassidy Dembele, Abdul-Aziz Yakubu (2017). Controlling imported malaria cases in the United States of America. Mathematical Biosciences and Engineering (MBE). https://doi.org/10.3934/mbe.2017007.

Colin Ponce, David S. Bindel (2017). FLiER: Practical Topology Update Detection Using Sparse PMUs. IEEE Transactions on Power Systems. https://doi.org/10.1109/TPWRS.2017.2662002. arXiv: 1409.6644. [pdf]

Frank A. La Sorte, Daniel Fink (2017). Projected changes in prevailing winds for transatlantic migratory birds under global warming. Journal of Animal Ecology. https://doi.org/10.1111/1365-2656.12624.

Natalie M. Mahowald, James T. Randerson, Keith Lindsay, Ernesto Munoz, Scott C. Doney, Peter Lawrence, ... Forrest M. Hoffman (2017). Interactions between land use change and carbon cycle feedbacks. Global Biochemical Cycles. https://doi.org/10.1002/2016GB005374.

Dana J. Morin, Angela K. Fuller, J. Andrew Royle, Chris Sutherland (2017). Model-based estimators of density and connectivity to inform conservation of spatially structured populations Authors. Ecosphere. https://doi.org/10.1002/ecs2.1623. [pdf]

József Z. Farkas, Stephen A. Gourley, Rongsong Liu, Abdul-Aziz Yakubu (2017). Modelling Wolbachia infection in a sex-structured mosquito population carrying West Nile virus. Journal of Math Biology. https://doi.org/10.1007/s00285-017-1096-7. [pdf]

Santosh K. Suram, Yexiang Xue, Junwen Bai, Ronan Le Bras, Brendan Rappazzo, Richard Bernstein, ... John M. Gregoire (2017). Automated Phase Mapping with AgileFD and its Application to Light Absorber Discovery in the V-Mn-Nb Oxide System. ACS Combinatorial Science. https://doi.org/10.1021/acscombsci.6b00153. [pdf]

ACS Editors' Choice

Nourridine Siewe, Abdul-Aziz Yakubu, Abhay R Satoskar, Avner Friedman (2017). Granuloma formation in leishmaniasis: A mathematical model. Journal of Theoretical Biology. https://doi.org/10.1016/j.jtbi.2016.10.004.

Chadi Saad-Roy, P. van den Driessche, Abdul-Aziz Yakubu (2016). A Mathematical Model of Anthrax Transmission in Animal Populations. Bulletin of Mathematical Biology. https://doi.org/10.1007/s11538-016-0238-1.

Nanjing Jian, Daniel Freund, Holly M. Wiberg, Shane G. Henderson (2016). Simulation optimization for a large-scale bike-sharing system. Proceedings of the 2016 Winter Simulation Conference. https://doi.org/10.1109/WSC.2016.7822125.

Ajitesh Jain, David Robinson, Bistra Dilkina, Richard Fujimoto (2016). An approach to integrate inter-dependent simulations using HLA with applications to sustainable urban development. Proceedings of the 2016 Winter Simulation Conference. https://doi.org/10.1109/WSC.2016.7822178.

Kevin Winner, Daniel Sheldon (2016). Probabilistic Inference with Generating Functions for Poisson Latent Variable Models. Neural Information Processing Systems (NIPS). [pdf]

Alnur Ali, J. Zico Kolter, Ryan J. Tibshirani (2016). The Multiple Quantile Graphical Model. Neural Information Processing Systems (NIPS). arXiv: 1607.00515. [pdf]

Frank A. La Sorte, Daniel Fink (2016). Migration distance, ecological barriers and en-route variation in the migratory behaviour of terrestrial bird populations. Global Ecology and Biogeography. https://doi.org/10.1111/geb.12534.

Debarun Kar, Fei Fang, Francesco M. Delle Fave, Nicole Sintov, Milind Tambe, Arnaud Lyet (2016). Comparing human behavior models in repeated Stackelberg security games: An extended study. Journal of Artificial Intelligence. https://doi.org/10.1016/j.artint.2016.08.002. [pdf]

Jingjing Liang, Thomas W. Crowther, Nicolas Picard, Susan Wiser, Mo Zhou, Giorgio Alberti, ... Peter B. Reich (2016). Positive biodiversity-productivity relationship predominant in global forests. Science. https://doi.org/10.1126/science.aaf8957. [pdf]

Shahrzad Gholami, Bryan Wilder, Matthew Brown, Dana Thomas, Nicole Sintov, Milind Tambe (2016). Divide to Defend: Collusive Security Games. GameSec 2016: Decision and Game Theory for Security. https://doi.org/10.1007/978-3-319-47413-7_16. [pdf]

Douglas H. Fisher, Zimei Bian, Selina Chen (2016). Incorporating Sustainability into Computing Education. IEEE Intelligent Systems. https://doi.org/10.1109/MIS.2016.76.

Bistra Dilkina, Rachel Houtman, Carla P. Gomes, Claire A. Montgomery, Kevin S. McKelvey, Katherine Kendall, ... Michael K. Schwartz (2016). Trade-offs and efficiencies in optimal budget-constrained multispecies corridor networks. Conservation Biology. https://doi.org/10.1111/cobi.12814.

Shahrzad Gholami, Bryan Wilder, Matthew Brown, Dana Thomas, Nicole Sintov, Milind Tambe (2016). Toward Addressing Collusion among Human Adversaries in Security Games. European Conference on Artificial Intelligence (ECAI). https://doi.org/10.3233/978-1-61499-672-9-1750. [pdf]

Judy Shamoun-Baranes, Andrew Farnsworth, Bart Aelterman, Jose A. Alves, Kevin Azijn, Garrett Bernstein, ... Hans van Gasteren (2016). Innovative Visualizations Shed Light on Avian Nocturnal Migration. PLOS ONE. https://doi.org/10.1371/journal.pone.0160106. [pdf]

Yexiang Xue, Ian Davies, Daniel Fink, Christopher Wood, Carla P. Gomes (2016). Behavior Identification in Two-Stage Games for Incentivizing Citizen Science Exploration. International Conference on Principles and Practice of Constraint Programming, CP 2016. https://doi.org/10.1007/978-3-319-44953-1_44. [pdf]

Neal Jean, Marshall Burke, Michael Xie, W. Matthew Davis, David B. Lobell, Stefano Ermon (2016). Combining satellite imagery and machine learning to predict poverty. Science. https://doi.org/10.1126/science.aaf7894.

Andrew Farnsworth, Benjamin M. Van Doren, Wesley M. Hochachka, Daniel Sheldon, Kevin Winner, Jed Irvine, ... Steve Kelling (2016). A characterization of autumn nocturnal migration detected by weather surveillance radars in the northeastern USA. Ecological Applications. https://doi.org/10.1890/15-0023.

Frank A. La Sorte, Wesley M. Hochachka, Andrew Farnsworth, André A. Dhondt, Daniel Sheldon (2016). The implications of mid-latitude climate extremes for North American migratory bird populations. Ecosphere. https://doi.org/10.1002/ecs2.1261. [pdf]

József Z. Farkas, Stephen A. Gourley, Rongsong Liu, Abdul-Aziz Yakubu (2016). Using mathematics at AIM to outwit mosquitoes. Notices of the AMS. [pdf]

Forrest Briggs, Xiaoli Fern, Raviv Raich, Matthew Betts (2016). Multi-Instance Multi Label Class Discovery: A Computational Approach for Assessing Bird Biodiversity. AAAI-16 Special Track on Computational Sustainability. [pdf]

Akshat Kumar, Arambam James Singh, Pradeep Varakantham, Daniel Sheldon (2016). Robust Decision Making for Stochastic Network Design. AAAI-16 Special Track on Computational Sustainability. [pdf]

Sara Marie Mc Carthy, Milind Tambe, Christopher Kiekintveld, Meredith L. Gore, Alex Killion (2016). Preventing Illegal Logging: Simultaneous Optimization of Resource Teams and Tactics for Security. AAAI-16 Special Track on Computational Sustainability. [pdf]

Xiaojian Wu, Daniel Sheldon, Shlomo Zilberstein (2016). Optimizing Resilience in Large Scale Networks. AAAI-16 Special Track on Computational Sustainability. [pdf]

Michael Xie, Neal Jean, Marshall Burke, David Lobell, Stefano Ermon (2016). Transfer Learning from Deep Features for Remote Sensing and Poverty Mapping. AAAI-16 Special Track on Computational Sustainability. arXiv: 1510.00098. [pdf]

Fei Fang, Thanh H. Nguyen, Rob Pickles, Wai Y. Lam, Gopalasamy R. Clements, Bo An, ... Milind Tambe (2016). Deploying PAWS to Combat Poaching: Game-Theoretic Patrolling in Areas with Complex Terrain (Demonstration). AAAI-16 Demonstration Papers. [pdf]

Fei Fang, Thanh H. Nguyen, Rob Pickles, Wai Y. Lam, Gopalasamy R. Clements, Bo An, ... Andrew Lemieux (2016). Deploying PAWS: Field Optimization of the Protection Assistant for Wildlife Security. Twenty-Eighth IAAI Conference. [pdf]

Deployed Application Award

Frank A. La Sorte, Daniel Fink, Wesley M. Hochachka, Steve Kelling (2016). Convergence of broad-scale migration strategies in terrestrial birds. Proceedings of the Royal Society B: Biological Sciences. https://doi.org/10.1098/rspb.2015.2588. [pdf]

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