| Detection as regression: Certified object detection with median smoothing P Chiang, M Curry, A Abdelkader, A Kumar, J Dickerson, T Goldstein Advances in Neural Information Processing Systems 33, 1275-1286, 2020 | 74 | 2020 |
| Certified neural network watermarks with randomized smoothing A Bansal, P Chiang, MJ Curry, R Jain, C Wigington, V Manjunatha, ... International Conference on Machine Learning, 1450-1465, 2022 | 54 | 2022 |
| Certifying strategyproof auction networks M Curry, PY Chiang, T Goldstein, J Dickerson Advances in Neural Information Processing Systems 33, 4987-4998, 2020 | 43 | 2020 |
| Preferencenet: Encoding human preferences in auction design with deep learning N Peri, M Curry, S Dooley, J Dickerson Advances in Neural Information Processing Systems 34, 17532-17542, 2021 | 38 | 2021 |
| Proportionnet: Balancing fairness and revenue for auction design with deep learning K Kuo, A Ostuni, E Horishny, MJ Curry, S Dooley, P Chiang, T Goldstein, ... arXiv preprint arXiv:2010.06398, 2020 | 35 | 2020 |
| Differentiable economics for randomized affine maximizer auctions M Curry, T Sandholm, J Dickerson arXiv preprint arXiv:2202.02872, 2022 | 34 | 2022 |
| A framework for the analysis of phantom data in multicenter diffusion tensor imaging studies L Walker, M Curry, A Nayak, N Lange, C Pierpaoli, ... Human brain mapping 34 (10), 2439-2454, 2013 | 34 | 2013 |
| Learning revenue-maximizing auctions with differentiable matching MJ Curry, U Lyi, T Goldstein, JP Dickerson International Conference on Artificial Intelligence and Statistics, 6062-6073, 2022 | 25 | 2022 |
| Learning Solutions in Large Economic Networks using Deep Multi-Agent Reinforcement Learning. M Curry, A Trott, S Phade, Y Bai, S Zheng AAMAS, 2760-2762, 2023 | 15* | 2023 |
| Vandermonde wave function ansatz for improved variational Monte Carlo A Acevedo, M Curry, SH Joshi, B Leroux, N Malaya 2020 IEEE/ACM Fourth Workshop on Deep Learning on Supercomputers (DLS), 40-47, 2020 | 11 | 2020 |
| Headless horseman: Adversarial attacks on transfer learning models A Abdelkader, MJ Curry, L Fowl, T Goldstein, A Schwarzschild, M Shu, ... ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 7 | 2020 |
| Truthful aggregation of llms with an application to online advertising E Soumalias, MJ Curry, S Seuken arXiv preprint arXiv:2405.05905, 2024 | 6 | 2024 |
| Automated design of affine maximizer mechanisms in dynamic settings M Curry, V Thoma, D Chakrabarti, S McAleer, C Kroer, T Sandholm, N He, ... Proceedings of the AAAI Conference on Artificial Intelligence 38 (9), 9626-9635, 2024 | 6 | 2024 |
| Improving policy-constrained kidney exchange via pre-screening D McElfresh, M Curry, T Sandholm, J Dickerson Advances in Neural Information Processing Systems 33, 2674-2685, 2020 | 6 | 2020 |
| Mix and match: Markov chains and mixing times for matching in rideshare M Curry, JP Dickerson, KA Sankararaman, A Srinivasan, Y Wan, P Xu Web and Internet Economics: 15th International Conference, WINE 2019, New …, 2019 | 6 | 2019 |
| Optimal automated market makers: Differentiable economics and strong duality MJ Curry, Z Fan, DC Parkes arXiv preprint arXiv:2402.09129, 2024 | 3 | 2024 |
| Scalable mechanism design for multi-agent path finding P Friedrich, Y Zhang, M Curry, L Dierks, S McAleer, J Li, T Sandholm, ... arXiv preprint arXiv:2401.17044, 2024 | 3 | 2024 |
| Learning best response policies in dynamic auctions via deep reinforcement learning V Thoma, M Curry, N He, S Seuken arXiv preprint arXiv:2312.13232, 2023 | 3 | 2023 |
| Soham Phade, Yu Bai, and Stephan Zheng. Analyzing Micro-Founded General Equilibrium Models with Many Agents Using Deep Reinforcement Learning M Curry, A Trott arXiv preprint arXiv:2201.01163, 2022 | 3 | 2022 |
| Scalable equilibrium computation in multi-agent influence games on networks F Christia, M Curry, C Daskalakis, E Demaine, JP Dickerson, ... Proceedings of the AAAI Conference on Artificial Intelligence 35 (6), 5277-5285, 2021 | 3 | 2021 |
