Jason Hartford
14 papers · 2017–2026 · 6 venues · across top CS/AI venues
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Machine Learning
(13)
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(6)
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(6)
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(5)
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Learning Types Β· Deep Learning
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Mathematics & Optimization
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Keywords
deep learning
(3)
causal inference
(3)
instrumental variable
(2)
experimental design
(2)
genetic perturbation
(2)
multimodal learning
(2)
end-to-end learning
(2)
representation learning
(1)
active learning
(1)
unsupervised learning
(1)
uncertainty quantification
(1)
in-context learning
(1)
domain adaptation
(1)
permutation equivariance
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nearest neighbor
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binary classification
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gaussian process
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kernel estimation
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contrastive learning
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pretraining
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Papers
Unpaired Multimodal Learning for Biological Datasets
MIDL 2026
Efficient Biological Data Acquisition through Inference Set Design
ICLR 2025
LLMs for Bayesian Optimization in Scientific Domains: Are We There Yet?
EMNLP 2025
Towards scientific discovery with dictionary learning: Extracting biological concepts from microscopy foundation models
ICML 2025
ViTally Consistent: Scaling Biological Representation Learning for Cell Microscopy
ICML 2025
Object centric architectures enable efficient causal representation learning
ICLR 2024
Propensity Score Alignment of Unpaired Multimodal Data
NeurIPS 2024
Targeted Sequential Indirect Experiment Design
NeurIPS 2024
Sequential Underspecified Instrument Selection for Cause-Effect Estimation
ICML 2023
Properties from mechanisms: an equivariance perspective on identifiable representation learning
ICLR 2022
The Perils of Learning Before Optimizing
AAAI 2022
Predicting Propositional Satisfiability via End-to-End Learning
AAAI 2020
Deep Models of Interactions Across Sets
ICML 2018
Deep IV: A Flexible Approach for Counterfactual Prediction
ICML 2017