| Thermometer encoding: One hot way to resist adversarial examples J Buckman, A Roy, C Raffel, I Goodfellow International Conference on Learning Representations, 2018 | 781 | 2018 |
| Sample-efficient reinforcement learning with stochastic ensemble value expansion J Buckman, D Hafner, G Tucker, E Brevdo, H Lee Advances in Neural Information Processing Systems, 8224-8234, 2018 | 408 | 2018 |
| DeepMDP: Learning continuous latent space models for representation learning C Gelada, S Kumar, J Buckman, O Nachum, MG Bellemare International Conference on Machine Learning, 2170-2179, 2019 | 348 | 2019 |
| The Importance of Pessimism in Fixed-Dataset Policy Optimization J Buckman, C Gelada, MG Bellemare Ninth International Conference on Learning Representations, 2020 | 161 | 2020 |
| Is generator conditioning causally related to GAN performance? A Odena, J Buckman, C Olsson, T Brown, C Olah, C Raffel, I Goodfellow International conference on machine learning, 3849-3858, 2018 | 145 | 2018 |
| When does return-conditioned supervised learning work for offline reinforcement learning? D Brandfonbrener, A Bietti, J Buckman, R Laroche, J Bruna Advances in Neural Information Processing Systems 35, 1542-1553, 2022 | 77 | 2022 |
| Neural lattice language models J Buckman, G Neubig Transactions of the Association for Computational Linguistics 6, 529-541, 2018 | 30 | 2018 |
| Transition-based dependency parsing with heuristic backtracking J Buckman, M Ballesteros, C Dyer Proceedings of the 2016 Conference on Empirical Methods in Natural Language …, 2016 | 11 | 2016 |
| Non-Markovian policies occupancy measures R Laroche, RT Combes, J Buckman arXiv preprint arXiv:2205.13950, 2022 | 4 | 2022 |
| Fair ML Tools Require Problematic ML Models J Buckman https://jacobbuckman.com/2021-02-15-fair-ml-tools-require-problematic-ml-models/, 2021 | 3 | 2021 |
| Neural Regression For Scale-Varying Targets A Khakhar, J Buckman arXiv preprint arXiv:2211.07447, 2022 | 1 | 2022 |
| Increasing security of neural networks by discretizing neural network inputs A Roy, I Goodfellow, J Buckman, CA Raffel US Patent 11,354,574, 2022 | | 2022 |
| Deep Autoregressive Regression. A Khakhar, J Buckman CoRR, 2022 | | 2022 |
Carles GeladaOpenAIVerified email at openai.com
Carles GeladaOpenAIVerified email at openai.com