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ORCIDJason S. Hartford
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Conference and Workshop Papers
- 2024
[c13]Chris Cameron, Jason S. Hartford, Taylor Lundy, Tuan Truong, Alan Milligan, Rex Chen, Kevin Leyton-Brown:
UNSAT Solver Synthesis via Monte Carlo Forest Search. CPAIOR (1) 2024: 170-189- [c12]Amin Mansouri, Jason S. Hartford, Yan Zhang, Yoshua Bengio:
Object centric architectures enable efficient causal representation learning. ICLR 2024 - 2023
- [c11]Elisabeth Ailer, Jason S. Hartford, Niki Kilbertus:
Sequential Underspecified Instrument Selection for Cause-Effect Estimation. ICML 2023: 408-420 - [c10]Lazar Atanackovic, Alexander Tong, Bo Wang, Leo J. Lee, Yoshua Bengio, Jason S. Hartford:
DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with GFlowNets. NeurIPS 2023 - 2022
- [c9]Chris Cameron, Jason S. Hartford, Taylor Lundy, Kevin Leyton-Brown:
The Perils of Learning Before Optimizing. AAAI 2022: 3708-3715 - [c8]Kartik Ahuja, Jason S. Hartford, Yoshua Bengio:
Properties from mechanisms: an equivariance perspective on identifiable representation learning. ICLR 2022 - [c7]Kartik Ahuja, Jason S. Hartford, Yoshua Bengio:
Weakly Supervised Representation Learning with Sparse Perturbations. NeurIPS 2022 - 2021
- [c6]Jason S. Hartford, Victor Veitch, Dhanya Sridhar, Kevin Leyton-Brown:
Valid Causal Inference with (Some) Invalid Instruments. ICML 2021: 4096-4106 - 2020
- [c5]Chris Cameron, Rex Chen
, Jason S. Hartford, Kevin Leyton-Brown:
Predicting Propositional Satisfiability via End-to-End Learning. AAAI 2020: 3324-3331 - [c4]Jason S. Hartford, Kevin Leyton-Brown, Hadas Raviv, Dan Padnos, Shahar Lev, Barak Lenz:
Exemplar Guided Active Learning. NeurIPS 2020 - 2018
- [c3]Jason S. Hartford, Devon R. Graham, Kevin Leyton-Brown, Siamak Ravanbakhsh:
Deep Models of Interactions Across Sets. ICML 2018: 1914-1923 - 2017
- [c2]Jason S. Hartford, Greg Lewis, Kevin Leyton-Brown, Matt Taddy:
Deep IV: A Flexible Approach for Counterfactual Prediction. ICML 2017: 1414-1423 - 2016
- [c1]Jason S. Hartford, James R. Wright, Kevin Leyton-Brown:
Deep Learning for Predicting Human Strategic Behavior. NIPS 2016: 2424-2432
Informal and Other Publications
- 2024
- [i16]Johnny Xi, Jason S. Hartford:
Propensity Score Alignment of Unpaired Multimodal Data. CoRR abs/2404.01595 (2024) - [i15]Elisabeth Ailer, Niclas Dern, Jason S. Hartford, Niki Kilbertus:
Targeted Sequential Indirect Experiment Design. CoRR abs/2405.19985 (2024) - [i14]Elliot Layne, Jason S. Hartford, Sébastien Lachapelle, Mathieu Blanchette, Dhanya Sridhar:
Leveraging Structure Between Environments: Phylogenetic Regularization Incentivizes Disentangled Representations. CoRR abs/2405.20482 (2024) - [i13]Zuheng Xu, Moksh Jain, Ali Denton, Shawn Whitfield, Aniket Didolkar, Berton Earnshaw, Jason S. Hartford:
Automated Discovery of Pairwise Interactions from Unstructured Data. CoRR abs/2409.07594 (2024) - 2023
- [i12]Moksh Jain, Tristan Deleu, Jason S. Hartford, Cheng-Hao Liu, Alex Hernández-García, Yoshua Bengio:
GFlowNets for AI-Driven Scientific Discovery. CoRR abs/2302.00615 (2023) - [i11]Lazar Atanackovic, Alexander Tong, Jason S. Hartford, Leo J. Lee, Bo Wang, Yoshua Bengio:
DynGFN: Bayesian Dynamic Causal Discovery using Generative Flow Networks. CoRR abs/2302.04178 (2023) - [i10]Elisabeth Ailer, Jason S. Hartford, Niki Kilbertus:
Sequential Underspecified Instrument Selection for Cause-Effect Estimation. CoRR abs/2302.05684 (2023) - [i9]Amin Mansouri, Jason S. Hartford, Yan Zhang, Yoshua Bengio:
Object-centric architectures enable efficient causal representation learning. CoRR abs/2310.19054 (2023) - 2022
- [i8]Kartik Ahuja, Jason S. Hartford, Yoshua Bengio:
Weakly Supervised Representation Learning with Sparse Perturbations. CoRR abs/2206.01101 (2022) - [i7]Chris Cameron, Jason S. Hartford, Taylor Lundy, Tuan Truong, Alan Milligan, Rex Chen, Kevin Leyton-Brown:
Monte Carlo Forest Search: UNSAT Solver Synthesis via Reinforcement learning. CoRR abs/2211.12581 (2022) - 2021
- [i6]Chris Cameron, Jason S. Hartford, Taylor Lundy, Kevin Leyton-Brown:
The Perils of Learning Before Optimizing. CoRR abs/2106.10349 (2021) - [i5]Kartik Ahuja, Jason S. Hartford, Yoshua Bengio:
Properties from Mechanisms: An Equivariance Perspective on Identifiable Representation Learning. CoRR abs/2110.15796 (2021) - 2020
- [i4]Jason S. Hartford, Victor Veitch, Dhanya Sridhar, Kevin Leyton-Brown:
Valid Causal Inference with (Some) Invalid Instruments. CoRR abs/2006.11386 (2020) - [i3]Jason S. Hartford, Kevin Leyton-Brown, Hadas Raviv, Dan Padnos, Shahar Lev, Barak Lenz:
Exemplar Guided Active Learning. CoRR abs/2011.01285 (2020) - 2018
- [i2]Jason S. Hartford, Devon R. Graham, Kevin Leyton-Brown, Siamak Ravanbakhsh:
Deep Models of Interactions Across Sets. CoRR abs/1803.02879 (2018) - 2016
- [i1]Jason S. Hartford, Greg Lewis, Kevin Leyton-Brown, Matt Taddy:
Counterfactual Prediction with Deep Instrumental Variables Networks. CoRR abs/1612.09596 (2016)
Coauthor Index
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