| BatchEnsemble: an alternative approach to efficient ensemble and lifelong learning Y Wen, D Tran, J Ba International Conference on Learning Representations (ICLR), 2020 | 515 | 2020 |
| Benchmarking model-based reinforcement learning T Wang, X Bao, I Clavera, J Hoang, Y Wen, E Langlois, S Zhang, G Zhang, ... arXiv preprint arXiv:1907.02057, 2019 | 485 | 2019 |
| Flipout: efficient pseudo-independent weight perturbations on mini-batches Y Wen, P Vicol, J Ba, D Tran, R Grosse International Conference on Learning Representations (ICLR), 2018 | 396 | 2018 |
| Efficient and scalable bayesian neural nets with rank-1 factors M Dusenberry, G Jerfel, Y Wen, Y Ma, J Snoek, K Heller, ... International Conference on Machine Learning (ICML), 2020 | 247 | 2020 |
| Uncertainty baselines: Benchmarks for uncertainty & robustness in deep learning Z Nado, N Band, M Collier, J Djolonga, MW Dusenberry, S Farquhar, ... arXiv preprint arXiv:2106.04015, 2021 | 114 | 2021 |
| Combining ensembles and data augmentation can harm your calibration Y Wen, G Jerfel, R Muller, MW Dusenberry, J Snoek, ... International Conference on Learning Representations (ICLR), 2020 | 76 | 2020 |
| An empirical study of stochastic gradient descent with structured covariance noise Y Wen, K Luk, M Gazeau, G Zhang, H Chan, J Ba International Conference on Artificial Intelligence and Statistics (AISTATS), 2020 | 57* | 2020 |
| A simple approach to improve single-model deep uncertainty via distance-awareness JZ Liu, S Padhy, J Ren, Z Lin, Y Wen, G Jerfel, Z Nado, J Snoek, D Tran, ... Journal of Machine Learning Research (JMLR), 2023 | 55 | 2023 |
| Natural language to code generation in interactive data science notebooks P Yin, WD Li, K Xiao, A Rao, Y Wen, K Shi, J Howland, P Bailey, ... ACL 2023, 2022 | 52 | 2022 |
| A language-agent approach to formal theorem-proving A Thakur, Y Wen, S Chaudhuri First Conference on Language Modeling (COLM), 2024, 2023 | 28* | 2023 |
| Neural program generation modulo static analysis R Mukherjee, Y Wen, D Chaudhari, TW Reps, S Chaudhuri, C Jermaine Advances in Neural Information Processing Systems (NeurIPS), 2021 | 23 | 2021 |
| Batched low-rank adaptation of foundation models Y Wen, S Chaudhuri International Conference on Learning Representations (ICLR), 2023 | 16 | 2023 |
| Grounding data science code generation with input-output specifications Y Wen, P Yin, K Shi, H Michalewski, S Chaudhuri, A Polozov arXiv preprint arXiv:2402.08073, 2024 | 8* | 2024 |
| Synthesize, Partition, then Adapt: Eliciting Diverse Samples from Foundation Models Y Wen, S Chaudhuri Advances in Neural Information Processing Systems (NeurIPS), 0 | | |
Jimmy BaUniversity of TorontoVerified email at cs.toronto.edu