| On empirical comparisons of optimizers for deep learning D Choi arXiv preprint arXiv:1910.05446, 2019 | 412 | 2019 |
| Backpropagation through the void: Optimizing control variates for black-box gradient estimation W Grathwohl, D Choi, Y Wu, G Roeder, D Duvenaud arXiv preprint arXiv:1711.00123, 2017 | 331 | 2017 |
| Guided evolutionary strategies: Augmenting random search with surrogate gradients N Maheswaranathan, L Metz, G Tucker, D Choi, J Sohl-Dickstein International Conference on Machine Learning, 4264-4273, 2019 | 101 | 2019 |
| Gradient estimation with stochastic softmax tricks M Paulus, D Choi, D Tarlow, A Krause, CJ Maddison Advances in neural information processing systems 33, 5691-5704, 2020 | 88 | 2020 |
| Faster neural network training with data echoing D Choi, A Passos, CJ Shallue, GE Dahl arXiv preprint arXiv:1907.05550, 2019 | 57 | 2019 |
| Guided evolutionary strategies: escaping the curse of dimensionality in random search N Maheswaranathan, L Metz, G Tucker, D Choi, J Sohl-Dickstein | 21 | 2018 |
| Tools for verifying neural models' training data D Choi, Y Shavit, DK Duvenaud Advances in Neural Information Processing Systems 36, 2024 | 10 | 2024 |
| On empirical comparisons of optimizers for deep learning: arXiv preprint, doi: 10. 48550 D Choi, CJ Shallue, Z Nado, J Lee, CJ Maddison, GE Dahl arxiv, 1910 | 10 | 1910 |
| Connecting the dots: Llms can infer and verbalize latent structure from disparate training data J Treutlein, D Choi, J Betley, S Marks, C Anil, R Grosse, O Evans arXiv preprint arXiv:2406.14546, 2024 | 9 | 2024 |
| LLM Processes: Numerical Predictive Distributions Conditioned on Natural Language J Requeima, J Bronskill, D Choi, RE Turner, D Duvenaud arXiv preprint arXiv:2405.12856, 2024 | 9 | 2024 |
| Self-tuning stochastic optimization with curvature-aware gradient filtering RTQ Chen, D Choi, L Balles, D Duvenaud, P Hennig PMLR, 2020 | 9 | 2020 |
| Order matters in the presence of dataset imbalance for multilingual learning D Choi, D Xin, H Dadkhahi, J Gilmer, A Garg, O Firat, CK Yeh, AM Dai, ... Advances in Neural Information Processing Systems 36, 2024 | 6 | 2024 |
| Systems and methods for reducing idleness in a machine-learning training system using data echoing D Choi, AT Passos, CJ Shallue, GE Dahl US Patent 11,537,949, 2022 | | 2022 |
