| 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 | 407* | 2017 |
| Deep models of interactions across sets J Hartford, D Graham, K Leyton-Brown, S Ravanbakhsh International Conference on Machine Learning, 1909-1918, 2018 | 136 | 2018 |
| Deep learning for predicting human strategic behavior JS Hartford, JR Wright, K Leyton-Brown Advances in neural information processing systems 29, 2016 | 84 | 2016 |
| 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 | 26 | 2020 |
| Valid causal inference with (some) invalid instruments JS Hartford, V Veitch, D Sridhar, K Leyton-Brown International Conference on Machine Learning, 4096-4106, 2021 | 15 | 2021 |
| Properties from mechanisms: an equivariance perspective on identifiable representation learning K Ahuja, J Hartford, Y Bengio arXiv preprint arXiv:2110.15796, 2021 | 13 | 2021 |
| Weakly supervised representation learning with sparse perturbations K Ahuja, JS Hartford, Y Bengio Advances in Neural Information Processing Systems 35, 15516-15528, 2022 | 8 | 2022 |
| 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 | 5 | 2022 |
| 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 |
| 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 | 2 | 2020 |
| GFlowNets for AI-driven scientific discovery M Jain, T Deleu, J Hartford, CH Liu, A Hernandez-Garcia, Y Bengio Digital Discovery, 2023 | 1 | 2023 |
| Monte Carlo Forest Search: UNSAT Solver Synthesis via Reinforcement learning C Cameron, J Hartford, T Lundy, T Truong, A Milligan, R Chen, ... arXiv preprint arXiv:2211.12581, 2022 | 1 | 2022 |
| Object-centric causal representation learning A Mansouri, J Hartford, K Ahuja, Y Bengio NeurIPS 2022 Workshop on Symmetry and Geometry in Neural Representations, 2022 | 1 | 2022 |
| Bayesian Dynamic Causal Discovery A Tong, L Atanackovic, J Hartford, Y Bengio A causal view on dynamical systems, NeurIPS 2022 workshop, 0 | 1 | |
| Finding the smallest tree in the forest: Monte Carlo Forest Search for UNSAT solving C Cameron, J Hartford, T Lundy, T Truong, A Milligan, R Chen, ... | | 2023 |
| Sequential Underspecified Instrument Selection for Cause-Effect Estimation E Ailer, J Hartford, N Kilbertus arXiv preprint arXiv:2302.05684, 2023 | | 2023 |
| DynGFN: Bayesian Dynamic Causal Discovery using Generative Flow Networks L Atanackovic, A Tong, J Hartford, LJ Lee, B Wang, Y Bengio arXiv preprint arXiv:2302.04178, 2023 | | 2023 |
| Architectures and learning algorithms for data-driven decision making JS Hartford University of British Columbia, 2021 | | 2021 |
| Unlocking the power of modern ML for use in CSP C Cameron, J Hartford, T Lundy, K Leyton-Brown | | |
| Deep Learning for Predicting Human Strategic Behavior-Supplementary Material J Hartford, JR Wright, K Leyton-Brown | | |
Kevin Leyton-BrownProfessor, Computer Science, University of British Columbia; Canada CIFAR AI ChairVerified email at cs.ubc.ca
