Jason S. Hartford

42 papers A* 16Journal 24Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
Elucidating the Design Space of Flow Matching for Cellular Microscopy.
CoRR
Charles Jones, Emmanuel Noutahi, Jason S. Hartford, Cian Eastwood
2025 A* conf
Efficient Biological Data Acquisition through Inference Set Design.
ICLR
Ihor Neporozhnii, Julien Roy, Emmanuel Bengio, Jason S. Hartford
2025 J jnl
Learning What Matters: Steering Diffusion via Spectrally Anisotropic Forward Noise.
CoRR
Luca Scimeca, Thomas Jiralerspong, Berton Earnshaw, Jason S. Hartford, Yoshua Bengio
2025 J jnl
Shaping Inductive Bias in Diffusion Models through Frequency-Based Noise Control.
CoRR
Thomas Jiralerspong, Berton Earnshaw, Jason S. Hartford, Yoshua Bengio, Luca Scimeca
2025 J jnl
Sparsity regularization via tree-structured environments for disentangled representations.
Trans. Mach. Learn. Res.
Elliot Layne, Jason S. Hartford, Sébastien Lachapelle, Mathieu Blanchette, Dhanya Sridhar
2025 A* conf
Towards scientific discovery with dictionary learning: Extracting biological concepts from microscopy foundation models.
ICML
Konstantin Donhauser, Kristina Ulicna, Gemma E. Moran, Aditya Ravuri, Kian Kenyon-Dean, Cian Eastwood, Jason S. Hartford
2025 A* conf
ViTally Consistent: Scaling Biological Representation Learning for Cell Microscopy.
ICML
Kian Kenyon-Dean, Zitong Jerry Wang, John Urbanik, Konstantin Donhauser, Jason S. Hartford, Saber Saberian, Nil Sahin, Ihab Bendidi, Safiye Celik, Juan Sebastián Rodríguez Vera, Marta M. Fay, Imran S. Haque, Oren Kraus
2025 J jnl
Virtual Cells: Predict, Explain, Discover.
CoRR
Emmanuel Noutahi, Jason S. Hartford, Prudencio Tossou, Shawn Whitfield, Alisandra Kaye Denton, Cas Wognum, Kristina Ulicna, Michael Craig, Jonathan Hsu, Michael Cuccarese, Emmanuel Bengio, Dominique Beaini, Christopher Gibson, Daniel Cohen, Berton Earnshaw
2024 J jnl
Automated Discovery of Pairwise Interactions from Unstructured Data.
CoRR
Zuheng Xu, Moksh Jain, Ali Denton, Shawn Whitfield, Aniket Didolkar, Berton Earnshaw, Jason S. Hartford
2024 J jnl
Efficient Biological Data Acquisition through Inference Set Design.
CoRR
Ihor Neporozhnii, Julien Roy, Emmanuel Bengio, Jason S. Hartford
2024 J jnl
Leveraging Structure Between Environments: Phylogenetic Regularization Incentivizes Disentangled Representations.
CoRR
Elliot Layne, Jason S. Hartford, Sébastien Lachapelle, Mathieu Blanchette, Dhanya Sridhar
2024 A* conf
Object centric architectures enable efficient causal representation learning.
ICLR
Amin Mansouri, Jason S. Hartford, Yan Zhang, Yoshua Bengio
2024 A* conf
Propensity Score Alignment of Unpaired Multimodal Data.
NeurIPS
Johnny Xi, Jana Osea, Zuheng Xu, Jason S. Hartford
2024 J jnl
Propensity Score Alignment of Unpaired Multimodal Data.
CoRR
Johnny Xi, Jason S. Hartford
2024 A* conf
Targeted Sequential Indirect Experiment Design.
NeurIPS
Elisabeth Ailer, Niclas Dern, Jason S. Hartford, Niki Kilbertus
2024 J jnl
Targeted Sequential Indirect Experiment Design.
CoRR
Elisabeth Ailer, Niclas Dern, Jason S. Hartford, Niki Kilbertus
2024 J jnl
Towards scientific discovery with dictionary learning: Extracting biological concepts from microscopy foundation models.
CoRR
Konstantin Donhauser, Kristina Ulicna, Gemma E. Moran, Aditya Ravuri, Kian Kenyon-Dean, Cian Eastwood, Jason S. Hartford
2024 — conf
UNSAT Solver Synthesis via Monte Carlo Forest Search.
CPAIOR (1)
Chris Cameron, Jason S. Hartford, Taylor Lundy, Tuan Truong, Alan Milligan, Rex Chen, Kevin Leyton-Brown
2024 J jnl
ViTally Consistent: Scaling Biological Representation Learning for Cell Microscopy.
CoRR
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 Sebastián Rodríguez Vera, Imran S. Haque, Oren Kraus
2023 J jnl
DynGFN: Bayesian Dynamic Causal Discovery using Generative Flow Networks.
CoRR
Lazar Atanackovic, Alexander Tong, Jason S. Hartford, Leo J. Lee, Bo Wang, Yoshua Bengio
2023 A* conf
DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with GFlowNets.
NeurIPS
Lazar Atanackovic, Alexander Tong, Bo Wang, Leo J. Lee, Yoshua Bengio, Jason S. Hartford
2023 J jnl
GFlowNets for AI-Driven Scientific Discovery.
CoRR
Moksh Jain, Tristan Deleu, Jason S. Hartford, Cheng-Hao Liu, Alex Hernández-García, Yoshua Bengio
2023 J jnl
Object-centric architectures enable efficient causal representation learning.
CoRR
Amin Mansouri, Jason S. Hartford, Yan Zhang, Yoshua Bengio
2023 A* conf
Sequential Underspecified Instrument Selection for Cause-Effect Estimation.
ICML
Elisabeth Ailer, Jason S. Hartford, Niki Kilbertus
2023 J jnl
Sequential Underspecified Instrument Selection for Cause-Effect Estimation.
CoRR
Elisabeth Ailer, Jason S. Hartford, Niki Kilbertus
2022 J jnl
Monte Carlo Forest Search: UNSAT Solver Synthesis via Reinforcement learning.
CoRR
Chris Cameron, Jason S. Hartford, Taylor Lundy, Tuan Truong, Alan Milligan, Rex Chen, Kevin Leyton-Brown
2022 A* conf
Properties from mechanisms: an equivariance perspective on identifiable representation learning.
ICLR
Kartik Ahuja, Jason S. Hartford, Yoshua Bengio
2022 A* conf
The Perils of Learning Before Optimizing.
AAAI
Chris Cameron, Jason S. Hartford, Taylor Lundy, Kevin Leyton-Brown
2022 A* conf
Weakly Supervised Representation Learning with Sparse Perturbations.
NeurIPS
Kartik Ahuja, Jason S. Hartford, Yoshua Bengio
2022 J jnl
Weakly Supervised Representation Learning with Sparse Perturbations.
CoRR
Kartik Ahuja, Jason S. Hartford, Yoshua Bengio
2021 J jnl
Properties from Mechanisms: An Equivariance Perspective on Identifiable Representation Learning.
CoRR
Kartik Ahuja, Jason S. Hartford, Yoshua Bengio
2021 J jnl
The Perils of Learning Before Optimizing.
CoRR
Chris Cameron, Jason S. Hartford, Taylor Lundy, Kevin Leyton-Brown
2021 A* conf
Valid Causal Inference with (Some) Invalid Instruments.
ICML
Jason S. Hartford, Victor Veitch, Dhanya Sridhar, Kevin Leyton-Brown
2020 A* conf
Exemplar Guided Active Learning.
NeurIPS
Jason S. Hartford, Kevin Leyton-Brown, Hadas Raviv, Dan Padnos, Shahar Lev, Barak Lenz
2020 J jnl
Exemplar Guided Active Learning.
CoRR
Jason S. Hartford, Kevin Leyton-Brown, Hadas Raviv, Dan Padnos, Shahar Lev, Barak Lenz
2020 A* conf
Predicting Propositional Satisfiability via End-to-End Learning.
AAAI
Chris Cameron, Rex Chen, Jason S. Hartford, Kevin Leyton-Brown
2020 J jnl
Valid Causal Inference with (Some) Invalid Instruments.
CoRR
Jason S. Hartford, Victor Veitch, Dhanya Sridhar, Kevin Leyton-Brown
2018 A* conf
Deep Models of Interactions Across Sets.
ICML
Jason S. Hartford, Devon R. Graham, Kevin Leyton-Brown, Siamak Ravanbakhsh
2018 J jnl
Deep Models of Interactions Across Sets.
CoRR
Jason S. Hartford, Devon R. Graham, Kevin Leyton-Brown, Siamak Ravanbakhsh
2017 A* conf
Deep IV: A Flexible Approach for Counterfactual Prediction.
ICML
Jason S. Hartford, Greg Lewis, Kevin Leyton-Brown, Matt Taddy
2016 J jnl
Counterfactual Prediction with Deep Instrumental Variables Networks.
CoRR
Jason S. Hartford, Greg Lewis, Kevin Leyton-Brown, Matt Taddy
2016 — conf
Deep Learning for Predicting Human Strategic Behavior.
NIPS
Jason S. Hartford, James R. Wright, Kevin Leyton-Brown