| PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization S Lofti, M Finzi, S Kapoor, A Potapczynski, M Goldblum, AG Wilson 36th Conference on Neural Information Processing Systems, 2022 | 37 | 2022 |
| Invertible Gaussian Reparameterization: Revisiting the Gumbel-Softmax A Potapczynski, G Loaiza-Ganem, JP Cunningham Advances in Neural Information Processing Systems 33, 12311-12321, 2020 | 18 | 2020 |
| Simple and Fast Group Robustness by Automatic Feature Reweighting S Qiu, A Potapczynski, P Izmailov, AG Wilson arXiv preprint arXiv:2306.11074, 2023 | 17 | 2023 |
| Bias-Free Scalable Gaussian Processes via Randomized Truncations A Potapczynski, L Wu, D Biderman, G Pleiss, JP Cunningham International Conference on Machine Learning, 8609-8619, 2021 | 17 | 2021 |
| Low-Precision Arithmetic for Fast Gaussian Processes W Maddox, A Potapczynski, AG Wilson 38th Conference on Uncertainty in Artificial Intelligence, 2022 | 7 | 2022 |
| A Stable and Scalable Method for Solving Initial Value PDEs with Neural Networks M Finzi, A Potapczynski, M Choptuik, AG Wilson arXiv preprint arXiv:2304.14994, 2023 | 6 | 2023 |
| CoLA: Exploiting Compositional Structure for Automatic and Efficient Numerical Linear Algebra A Potapczynski, M Finzi, G Pleiss, AG Wilson arXiv preprint arXiv:2309.03060, 2023 | 2 | 2023 |
| On the Normalizing Constant of the Continuous Categorical Distribution E Gordon-Rodriguez, G Loaiza-Ganem, A Potapczynski, JP Cunningham arXiv preprint arXiv:2204.13290, 2022 | 1 | 2022 |
| OMI Research Newsletter–May 2023 M FINZI, A POTAPCZYNSKI, M CHOPTUIK, AG WILSON | | |
| Understanding the Generalization of Deep Neural Networks through PAC-Bayes bounds: A Survey A Potapczynski, S Lotfi, A Chen, C Ick | | |
| Supplementary Materials for Low Precision Arithmetic for Fast Gaussian Processes WJ Maddox, A Potapczynski, AG Wilson Order 10 (16), 10-12, 0 | | |
Andrew Gordon WilsonNew York UniversityVerified email at cims.nyu.edu
