Jason S. Hartford

According to our database, Jason S. Hartford authored at least 28 papers between 2016 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Virtual Cells: Predict, Explain, Discover.

Emmanuel Noutahi, Jason S. Hartford, Prudencio Tossou, Shawn Whitfield, Alisandra K. Denton, Cas Wognum, Kristina Ulicna, Michael Craig, Jonathan Hsu, Michael Cuccarese, Emmanuel Bengio, Dominique Beaini, Christopher Gibson, Daniel Cohen, Berton Earnshaw

CoRR, May, 2025

Shaping Inductive Bias in Diffusion Models through Frequency-Based Noise Control.

Thomas Jiralerspong, Berton Earnshaw, Jason S. Hartford, Yoshua Bengio, Luca Scimeca

CoRR, February, 2025

Sparsity regularization via tree-structured environments for disentangled representations.

Elliot Layne, Jason S. Hartford, Sébastien Lachapelle, Mathieu Blanchette, Dhanya Sridhar

Trans. Mach. Learn. Res., 2025

Efficient Biological Data Acquisition through Inference Set Design.

Ihor Neporozhnii, Julien Roy, Emmanuel Bengio, Jason S. Hartford

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Towards scientific discovery with dictionary learning: Extracting biological concepts from microscopy foundation models.

Konstantin Donhauser, Kristina Ulicna, Gemma E. Moran, Aditya Ravuri, Kian Kenyon-Dean, Cian Eastwood, Jason S. Hartford

CoRR, 2024

ViTally Consistent: Scaling Biological Representation Learning for Cell Microscopy.

Kian Kenyon-Dean, Zitong Jerry Wang, John Urbanik, Konstantin Donhauser, Jason S. Hartford, Saber Saberian, Nil Sahin, Ihab Bendidi, Safiye Celik, Marta M. Fay, Juan Sebastian Rodriguez Vera, Imran S. Haque, Oren Kraus

CoRR, 2024

Automated Discovery of Pairwise Interactions from Unstructured Data.

Zuheng Xu, Moksh Jain, Ali Denton, Shawn Whitfield, Aniket Didolkar, Berton Earnshaw, Jason S. Hartford

CoRR, 2024

Leveraging Structure Between Environments: Phylogenetic Regularization Incentivizes Disentangled Representations.

Elliot Layne, Jason S. Hartford, Sébastien Lachapelle, Mathieu Blanchette, Dhanya Sridhar

CoRR, 2024

Propensity Score Alignment of Unpaired Multimodal Data.

Johnny Xi, Jason S. Hartford

CoRR, 2024

Propensity Score Alignment of Unpaired Multimodal Data.

Johnny Xi, Jana Osea, Zuheng Xu, Jason S. Hartford

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Targeted Sequential Indirect Experiment Design.

Elisabeth Ailer, Niclas Dern, Jason S. Hartford, Niki Kilbertus

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Object centric architectures enable efficient causal representation learning.

Amin Mansouri, Jason S. Hartford, Yan Zhang, Yoshua Bengio

Proceedings of the Twelfth International Conference on Learning Representations, 2024

UNSAT Solver Synthesis via Monte Carlo Forest Search.

Chris Cameron, Jason S. Hartford, Taylor Lundy, Tuan Truong, Alan Milligan, Rex Chen, Kevin Leyton-Brown

Proceedings of the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 2024

2023

DynGFN: Bayesian Dynamic Causal Discovery using Generative Flow Networks.

Lazar Atanackovic, Alexander Tong, Jason S. Hartford, Leo J. Lee, Bo Wang, Yoshua Bengio

CoRR, 2023

GFlowNets for AI-Driven Scientific Discovery.

Moksh Jain, Tristan Deleu, Jason S. Hartford, Cheng-Hao Liu, Alex Hernández-García, Yoshua Bengio

CoRR, 2023

DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with GFlowNets.

Lazar Atanackovic, Alexander Tong, Bo Wang, Leo J. Lee, Yoshua Bengio, Jason S. Hartford

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Sequential Underspecified Instrument Selection for Cause-Effect Estimation.

Elisabeth Ailer, Jason S. Hartford, Niki Kilbertus

Proceedings of the International Conference on Machine Learning, 2023

2022

Monte Carlo Forest Search: UNSAT Solver Synthesis via Reinforcement learning.

Chris Cameron, Jason S. Hartford, Taylor Lundy, Tuan Truong, Alan Milligan, Rex Chen, Kevin Leyton-Brown

CoRR, 2022

Weakly Supervised Representation Learning with Sparse Perturbations.

Kartik Ahuja, Jason S. Hartford, Yoshua Bengio

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Properties from mechanisms: an equivariance perspective on identifiable representation learning.

Kartik Ahuja, Jason S. Hartford, Yoshua Bengio

Proceedings of the Tenth International Conference on Learning Representations, 2022

The Perils of Learning Before Optimizing.

Chris Cameron, Jason S. Hartford, Taylor Lundy, Kevin Leyton-Brown

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Valid Causal Inference with (Some) Invalid Instruments.

Jason S. Hartford, Victor Veitch, Dhanya Sridhar, Kevin Leyton-Brown

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Exemplar Guided Active Learning.

Jason S. Hartford, Kevin Leyton-Brown, Hadas Raviv, Dan Padnos, Shahar Lev, Barak Lenz

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Predicting Propositional Satisfiability via End-to-End Learning.

Chris Cameron, Rex Chen, Jason S. Hartford, Kevin Leyton-Brown

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2018

Deep Models of Interactions Across Sets.

Jason S. Hartford, Devon R. Graham, Kevin Leyton-Brown, Siamak Ravanbakhsh

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Deep IV: A Flexible Approach for Counterfactual Prediction.

Jason S. Hartford, Greg Lewis, Kevin Leyton-Brown, Matt Taddy

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Counterfactual Prediction with Deep Instrumental Variables Networks.

Jason S. Hartford, Greg Lewis, Kevin Leyton-Brown, Matt Taddy

CoRR, 2016

Deep Learning for Predicting Human Strategic Behavior.

Jason S. Hartford, James R. Wright, Kevin Leyton-Brown

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016