| Deep IV: A flexible approach for counterfactual prediction J Hartford, G Lewis, K Leyton-Brown, M Taddy International Conference on Machine Learning, 1414-1423, 2017 | 569* | 2017 |
| Deep models of interactions across sets J Hartford, D Graham, K Leyton-Brown, S Ravanbakhsh International Conference on Machine Learning, 1909-1918, 2018 | 169 | 2018 |
| Deep learning for predicting human strategic behavior JS Hartford, JR Wright, K Leyton-Brown Advances in neural information processing systems 29, 2016 | 105 | 2016 |
| Weakly supervised representation learning with sparse perturbations K Ahuja, JS Hartford, Y Bengio Advances in Neural Information Processing Systems 35, 15516-15528, 2022 | 51 | 2022 |
| Predicting propositional satisfiability via end-to-end learning C Cameron, R Chen, J Hartford, K Leyton-Brown Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3324-3331, 2020 | 35 | 2020 |
| Gflownets for ai-driven scientific discovery M Jain, T Deleu, J Hartford, CH Liu, A Hernandez-Garcia, Y Bengio Digital Discovery 2 (3), 557-577, 2023 | 33 | 2023 |
| Properties from mechanisms: an equivariance perspective on identifiable representation learning K Ahuja, J Hartford, Y Bengio arXiv preprint arXiv:2110.15796, 2021 | 32 | 2021 |
| Valid causal inference with (some) invalid instruments JS Hartford, V Veitch, D Sridhar, K Leyton-Brown International Conference on Machine Learning, 4096-4106, 2021 | 23 | 2021 |
| DynGFN: Towards bayesian inference of gene regulatory networks with gflownets L Atanackovic, A Tong, B Wang, LJ Lee, Y Bengio, JS Hartford Advances in Neural Information Processing Systems 36, 2024 | 18* | 2024 |
| The perils of learning before optimizing C Cameron, J Hartford, T Lundy, K Leyton-Brown Proceedings of the AAAI Conference on Artificial Intelligence 36 (4), 3708-3715, 2022 | 17 | 2022 |
| Object-centric architectures enable efficient causal representation learning A Mansouri, J Hartford, Y Zhang, Y Bengio arXiv preprint arXiv:2310.19054, 2023 | 8* | 2023 |
| UNSAT Solver Synthesis via Monte Carlo Forest Search C Cameron, J Hartford, T Lundy, T Truong, A Milligan, R Chen, ... International Conference on the Integration of Constraint Programming …, 2024 | 5* | 2024 |
| Exemplar guided active learning JS Hartford, K Leyton-Brown, H Raviv, D Padnos, S Lev, B Lenz Advances in Neural Information Processing Systems 33, 13163-13173, 2020 | 4 | 2020 |
| Sequential underspecified instrument selection for cause-effect estimation E Ailer, J Hartford, N Kilbertus International Conference on Machine Learning, 408-420, 2023 | 3 | 2023 |
| Who’s afraid of the big bad Wolf? Risk aversion and gender discrimination in assessment J Hartford, N Spearman Economic Research Southern Africa Working Papers, 2014 | 3 | 2014 |
| A novel and efficient machine learning Mendelian randomization estimator applied to predict the safety and efficacy of sclerostin inhibition MA Legault, J Hartford, BJ Arsenault, AY Yang, J Pineau medRxiv, 2024.01. 30.24302021, 2024 | 1 | 2024 |
| Targeted Sequential Indirect Experiment Design E Ailer, N Dern, J Hartford, N Kilbertus arXiv preprint arXiv:2405.19985, 2024 | | 2024 |
| Leveraging Structure Between Environments: Phylogenetic Regularization Incentivizes Disentangled Representations E Layne, J Hartford, S Lachapelle, M Blanchette, D Sridhar arXiv preprint arXiv:2405.20482, 2024 | | 2024 |
| Propensity Score Alignment of Unpaired Multimodal Data J Xi, J Hartford arXiv preprint arXiv:2404.01595, 2024 | | 2024 |
| Architectures and learning algorithms for data-driven decision making JS Hartford University of British Columbia, 2021 | | 2021 |
Kevin Leyton-BrownProfessor, Computer Science, University of British Columbia; Canada CIFAR AI Chair在 cs.ubc.ca 的电子邮件经过验证
