Jason S. Hartford

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 22

Top Topics

Bayesian Inference

Markovian Decision

Top Venues

Publications

Elisabeth Ailer, Niclas Dern, Jason S. Hartford, Niki Kilbertus
Targeted Sequential Indirect Experiment Design. CoRR (2024)
Elliot Layne, Jason S. Hartford, Sébastien Lachapelle, Mathieu Blanchette, Dhanya Sridhar
Leveraging Structure Between Environments: Phylogenetic Regularization Incentivizes Disentangled Representations. CoRR (2024)
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)
Amin Mansouri, Jason S. Hartford, Yan Zhang, Yoshua Bengio
Object centric architectures enable efficient causal representation learning. ICLR (2024)
Johnny Xi, Jason S. Hartford
Propensity Score Alignment of Unpaired Multimodal Data. CoRR (2024)
Amin Mansouri, Jason S. Hartford, Yan Zhang, Yoshua Bengio
Object-centric architectures enable efficient causal representation learning. CoRR (2023)
Elisabeth Ailer, Jason S. Hartford, Niki Kilbertus
Sequential Underspecified Instrument Selection for Cause-Effect Estimation. ICML (2023)
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)
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 (2022)
Chris Cameron, Jason S. Hartford, Taylor Lundy, Kevin Leyton-Brown
The Perils of Learning Before Optimizing. AAAI (2022)
Kartik Ahuja, Jason S. Hartford, Yoshua Bengio
Weakly Supervised Representation Learning with Sparse Perturbations. NeurIPS (2022)
Jason S. Hartford, Victor Veitch, Dhanya Sridhar, Kevin Leyton-Brown
Valid Causal Inference with (Some) Invalid Instruments. ICML (2021)
Chris Cameron, Jason S. Hartford, Taylor Lundy, Kevin Leyton-Brown
The Perils of Learning Before Optimizing. CoRR (2021)
Jason S. Hartford, Kevin Leyton-Brown, Hadas Raviv, Dan Padnos, Shahar Lev, Barak Lenz
Exemplar Guided Active Learning. CoRR (2020)
Chris Cameron, Rex Chen, Jason S. Hartford, Kevin Leyton-Brown
Predicting Propositional Satisfiability via End-to-End Learning. AAAI (2020)
Jason S. Hartford, Victor Veitch, Dhanya Sridhar, Kevin Leyton-Brown
Valid Causal Inference with (Some) Invalid Instruments. CoRR (2020)
Jason S. Hartford, Kevin Leyton-Brown, Hadas Raviv, Dan Padnos, Shahar Lev, Barak Lenz
Exemplar Guided Active Learning. NeurIPS (2020)
Jason S. Hartford, Devon R. Graham, Kevin Leyton-Brown, Siamak Ravanbakhsh
Deep Models of Interactions Across Sets. ICML (2018)
Jason S. Hartford, Devon R. Graham, Kevin Leyton-Brown, Siamak Ravanbakhsh
Deep Models of Interactions Across Sets. CoRR (2018)
Jason S. Hartford, Greg Lewis, Kevin Leyton-Brown, Matt Taddy
Deep IV: A Flexible Approach for Counterfactual Prediction. ICML (2017)
Jason S. Hartford, Greg Lewis, Kevin Leyton-Brown, Matt Taddy
Counterfactual Prediction with Deep Instrumental Variables Networks. CoRR (2016)
Jason S. Hartford, James R. Wright, Kevin Leyton-Brown
Deep Learning for Predicting Human Strategic Behavior. NIPS (2016)