| Measuring calibration in deep learning. J Nixon, MW Dusenberry, L Zhang, G Jerfel, D Tran CVPR workshops 2 (7), 2019 | 409 | 2019 |
| Understanding and correcting pathologies in the training of learned optimizers L Metz, N Maheswaranathan, J Nixon, D Freeman, J Sohl-Dickstein International Conference on Machine Learning, 4556-4565, 2019 | 140 | 2019 |
| Analyzing the role of model uncertainty for electronic health records MW Dusenberry, D Tran, E Choi, J Kemp, J Nixon, G Jerfel, K Heller, ... Proceedings of the ACM Conference on Health, Inference, and Learning, 204-213, 2020 | 103 | 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 | 98 | 2021 |
| What are you optimizing for? aligning recommender systems with human values J Stray, I Vendrov, J Nixon, S Adler, D Hadfield-Menell arXiv preprint arXiv:2107.10939, 2021 | 63 | 2021 |
| Why are bootstrapped deep ensembles not better? J Nixon, B Lakshminarayanan, D Tran ''I Can't Believe It's Not Better!''NeurIPS 2020 workshop, 2020 | 24 | 2020 |
| Resolving spurious correlations in causal models of environments via interventions S Volodin, N Wichers, J Nixon arXiv preprint arXiv:2002.05217, 2020 | 17 | 2020 |
| Training optimizer neural networks J Nixon, JN Sohl-Dickstein, LS Metz, CD Freeman, N Maheswaranathan US Patent App. 16/586,220, 2020 | 13 | 2020 |
| Robustness Metrics, 2020 J Djolonga, F Hubis, M Minderer, Z Nado, J Nixon, R Romijnders, D Tran, ... URL https://github. com/google-research/robustness_metrics, 0 | 9 | |
| Learned optimizers that outperform SGD on wall-clock and test loss L Metz, N Maheswaranathan, J Nixon, D Freeman, J Sohl-Dickstein Proceedings of the 2nd Workshop on Meta-Learning, MetaLearn 2019, 2018 | 7 | 2018 |
| Learned optimizers that outperform sgd on wall-clock and validation loss L Metz, N Maheswaranathan, J Nixon, CD Freeman, J Sohl-Dickstein arXiv preprint arXiv:1810.10180, 2018 | 6 | 2018 |
| Semi-supervised class discovery J Nixon, J Liu, D Berthelot arXiv preprint arXiv:2002.03480, 2020 | 3 | 2020 |
| Learned optimizers that outperform on wall-clock and validation loss L Metz, N Maheswaranathan, J Nixon, D Freeman, J Sohl-dickstein | | 2018 |
