Romain Lopez
12 papers · 2018–2025 · 5 venues · across top CS/AI venues
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Machine Learning
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(5)
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causal inference
(3)
variational inference
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variational autoencoder
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bandit feedback
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causal discovery
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importance sampling
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disentangled representation
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policy optimization
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graphical model
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reward function
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hilbert-schmidt independence criterion
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decision making
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causal structure learning
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multi-objective optimization
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flow matching
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nonlinear independent component analysis
(1)
cyclic causal model
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policy learning
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posterior approximation
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conditional independence
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Papers
Cross-modality Matching and Prediction of Perturbation Responses with Labeled Gromov-Wasserstein Optimal Transport
AISTATS 2025
Modeling Complex System Dynamics with Flow Matching Across Time and Conditions
ICLR 2025
GFlowNet Assisted Biological Sequence Editing
NeurIPS 2024
Learning Identifiable Factorized Causal Representations of Cellular Responses
NeurIPS 2024
Toward the Identifiability of Comparative Deep Generative Models
CLeaR 2024
Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling
CLeaR 2023
NODAGS-Flow: Nonlinear Cyclic Causal Structure Learning
AISTATS 2023
Large-Scale Differentiable Causal Discovery of Factor Graphs
NeurIPS 2022
Learning from eXtreme Bandit Feedback
AAAI 2021
Cost-Effective Incentive Allocation via Structured Counterfactual Inference
AAAI 2020
Decision-Making with Auto-Encoding Variational Bayes
NeurIPS 2020
Information Constraints on Auto-Encoding Variational Bayes
NeurIPS 2018