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Jason Hartford
Jason Hartford
Staff Machine Learning Research Scientist at Valence Labs / Recursion Pharma
Verifierad e-postadress på cs.ubc.ca - Startsida
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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
581*2017
Deep models of interactions across sets
J Hartford, D Graham, K Leyton-Brown, S Ravanbakhsh
International Conference on Machine Learning, 1909-1918, 2018
1582018
Deep learning for predicting human strategic behavior
JS Hartford, JR Wright, K Leyton-Brown
Advances in neural information processing systems 29, 2016
1012016
Weakly supervised representation learning with sparse perturbations
K Ahuja, JS Hartford, Y Bengio
Advances in Neural Information Processing Systems 35, 15516-15528, 2022
442022
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
342020
Properties from mechanisms: an equivariance perspective on identifiable representation learning
K Ahuja, J Hartford, Y Bengio
arXiv preprint arXiv:2110.15796, 2021
302021
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
242023
Valid causal inference with (some) invalid instruments
JS Hartford, V Veitch, D Sridhar, K Leyton-Brown
International Conference on Machine Learning, 4096-4106, 2021
192021
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
152022
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
6*2024
Object-centric architectures enable efficient causal representation learning
A Mansouri, J Hartford, Y Zhang, Y Bengio
arXiv preprint arXiv:2310.19054, 2023
6*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 (to appear November 21st), 2022
42022
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
32020
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
32014
Bayesian dynamic causal discovery
A Tong, L Atanackovic, J Hartford, Y Bengio
A causal view on dynamical systems, NeurIPS 2022 workshop, 2022
22022
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
2024
Sequential underspecified instrument selection for cause-effect estimation
E Ailer, J Hartford, N Kilbertus
International Conference on Machine Learning, 408-420, 2023
2023
UNSAT Solver Synthesis via Monte Carlo Forest Search
C Cameron, J Hartford, T Lundy, T Truong, A Milligan, R Chen, ...
arXiv preprint arXiv:2211.12581, 2022
2022
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, ...
2022
Beyond the injective assumption in causal representation learning
J Hartford, K Ahuja, Y Bengio, D Sridhar
2022
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Artiklar 1–20