| On the opportunities and risks of foundation models R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258, 2021 | 3758 | 2021 |
| A symbolic approach to explaining Bayesian network classifiers A Shih, A Choi, A Darwiche 27th International Joint Conference on Artificial Intelligence, 2018 | 267 | 2018 |
| Compiling Bayesian Network Classifiers into Decision Graphs A Shih, A Choi, A Darwiche Proceedings of the AAAI Conference on Artificial Intelligence 33, 7966-7974, 2019 | 83 | 2019 |
| On Tractable Representations of Binary Neural Networks W Shi, A Shih, A Darwiche, A Choi 17th International Conference on Principles of Knowledge Representation and …, 2020 | 73 | 2020 |
| Verifying binarized neural networks by angluin-style learning A Shih, A Darwiche, A Choi Theory and Applications of Satisfiability Testing–SAT 2019: 22nd …, 2019 | 67* | 2019 |
| Formal verification of Bayesian network classifiers A Shih, A Choi, A Darwiche International Conference on Probabilistic Graphical Models, 427-438, 2018 | 44 | 2018 |
| Imitation Learning by Estimating Expertise of Demonstrators M Beliaev, A Shih, S Ermon, D Sadigh, R Pedarsani International Conference on Machine Learning, 2022 | 42 | 2022 |
| On The Critical Role Of Conventions In Adaptive Human-AI Collaboration A Shih, A Sawhney, J Kondic, S Ermon, D Sadigh International Conference on Learning Representations (ICLR), 2021 | 41 | 2021 |
| Influencing Towards Stable Multi-Agent Interactions WZ Wang, A Shih, A Xie, D Sadigh Conference on Robot Learning (CoRL), 2021 | 33 | 2021 |
| On symbolically encoding the behavior of random forests A Choi, A Shih, A Goyanka, A Darwiche 3rd Workshop on Formal Methods for ML-Enabled Autonomous Systems (FoMLAS), 2020 | 32 | 2020 |
| Smoothing structured decomposable circuits A Shih, G Van den Broeck, P Beame, A Amarilli Advances in Neural Information Processing Systems, 11416-11426, 2019 | 30 | 2019 |
| Compiling neural networks into tractable Boolean circuits A Choi, W Shi, A Shih, A Darwiche AAAI Spring Symposium on Verification of Neural Networks (VNN), 2019 | 30 | 2019 |
| Parallel sampling of diffusion models A Shih, S Belkhale, S Ermon, D Sadigh, N Anari Advances in Neural Information Processing Systems 36, 2024 | 25 | 2024 |
| Probabilistic Circuits for Variational Inference in Discrete Graphical Models A Shih, S Ermon Advances in Neural Information Processing Systems 33, 2020 | 21 | 2020 |
| PantheonRL: A MARL Library for Dynamic Training Interactions B Sarkar, A Talati, A Shih, D Sadigh 36th AAAI Conference on Artificial Intelligence (Demo Track), 2021 | 18 | 2021 |
| Conditional Imitation Learning for Multi-Agent Games A Shih, S Ermon, D Sadigh 17th ACM/IEEE International Conference on Human-Robot Interaction, 2022 | 13 | 2022 |
| HyperSPNs: Compact and Expressive Probabilistic Circuits A Shih, D Sadigh, S Ermon Advances in Neural Information Processing Systems 34, 2021 | 11 | 2021 |
| Dreampropeller: Supercharge text-to-3d generation with parallel sampling L Zhou, A Shih, C Meng, S Ermon Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 10 | 2024 |
| Training and Inference on Any-Order Autoregressive Models the Right Way A Shih, D Sadigh, S Ermon Advances in Neural Information Processing Systems 35, 2022 | 10 | 2022 |
| Long horizon temperature scaling A Shih, D Sadigh, S Ermon International Conference on Machine Learning, 31422-31434, 2023 | 8 | 2023 |
