Romain Lopez

32 papers A* 8A 2B 1Journal 14Unranked 6
YearRankTypeTitle / Venue / Authors
2025 A conf
Cross-modality Matching and Prediction of Perturbation Responses with Labeled Gromov-Wasserstein Optimal Transport.
AISTATS
Jayoung Ryu, Charlotte Bunne, Luca Pinello, Aviv Regev, Romain Lopez
2025 A* conf
Modeling Complex System Dynamics with Flow Matching Across Time and Conditions.
ICLR
Martin Rohbeck, Edward De Brouwer, Charlotte Bunne, Jan-Christian Huetter, Anne Biton, Kelvin Y. Chen, Aviv Regev, Romain Lopez
2025 J jnl
Supervised Contrastive Block Disentanglement.
CoRR
Taro Makino, Ji Won Park, Natasa Tagasovska, Takamasa Kudo, Paula Coelho, Jan-Christian Huetter, Heming Yao, Burkhard Hoeckendorf, Ana Carolina Leote, Stephen Ra, David Richmond, Kyunghyun Cho, Aviv Regev, Romain Lopez
2024 A* conf
GFlowNet Assisted Biological Sequence Editing.
NeurIPS
Pouya M. Ghari, Alex M. Tseng, Gökcen Eraslan, Romain Lopez, Tommaso Biancalani, Gabriele Scalia, Ehsan Hajiramezanali
2024 — conf
Gene-Level Representation Learning via Interventional Style Transfer in Optical Pooled Screening.
CVPR Workshops
Mahtab Bigverdi, Burkhard Höckendorf, Heming Yao, Phil Hanslovsky, Romain Lopez, David Richmond
2024 J jnl
Gene-Level Representation Learning via Interventional Style Transfer in Optical Pooled Screening.
CoRR
Mahtab Bigverdi, Burkhard Hockendorf, Heming Yao, Phil Hanslovsky, Romain Lopez, David Richmond
2024 A* conf
Learning Identifiable Factorized Causal Representations of Cellular Responses.
NeurIPS
Haiyi Mao, Romain Lopez, Kai Liu, Jan-Christian Huetter, David Richmond, Panayiotis V. Benos, Lin Qiu
2024 J jnl
Learning Identifiable Factorized Causal Representations of Cellular Responses.
CoRR
Haiyi Mao, Romain Lopez, Kai Liu, Jan-Christian Hütter, David Richmond, Panayiotis V. Benos, Lin Qiu
2024 B conf
Sequential Optimal Experimental Design of Perturbation Screens Guided by Multi-modal Priors.
RECOMB
Kexin Huang, Romain Lopez, Jan-Christian Hütter, Takamasa Kudo, Antonio Rios, Aviv Regev
2024 — conf
Toward the Identifiability of Comparative Deep Generative Models.
CLeaR
Romain Lopez, Jan-Christian Hütter, Ehsan Hajiramezanali, Jonathan K. Pritchard, Aviv Regev
2024 J jnl
Toward the Identifiability of Comparative Deep Generative Models.
CoRR
Romain Lopez, Jan-Christian Hütter, Ehsan Hajiramezanali, Jonathan K. Pritchard, Aviv Regev
2023 — conf
A Supervised Contrastive Framework for Learning Disentangled Representations of Cellular Perturbation Data.
MLCB
Xinming Tu, Jan-Christian Hütter, Zitong Jerry Wang, Takamasa Kudo, Aviv Regev, Romain Lopez
2023 — conf
Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling.
CLeaR
Romain Lopez, Natasa Tagasovska, Stephen Ra, Kyunghyun Cho, Jonathan K. Pritchard, Aviv Regev
2023 A conf
NODAGS-Flow: Nonlinear Cyclic Causal Structure Learning.
AISTATS
Muralikrishnna G. Sethuraman, Romain Lopez, Rahul Mohan, Faramarz Fekri, Tommaso Biancalani, Jan-Christian Hütter
2023 J jnl
NODAGS-Flow: Nonlinear Cyclic Causal Structure Learning.
CoRR
Muralikrishnna G. Sethuraman, Romain Lopez, Rahul Mohan, Faramarz Fekri, Tommaso Biancalani, Jan-Christian Hütter
2022 — conf
Disentangling shared and group-specific variations in single-cell transcriptomics data with multiGroupVI.
MLCB
Ethan Weinberger, Romain Lopez, Jan-Christian Hütter, Aviv Regev
2022 A* conf
Large-Scale Differentiable Causal Discovery of Factor Graphs.
NeurIPS
Romain Lopez, Jan-Christian Hütter, Jonathan K. Pritchard, Aviv Regev
2022 J jnl
Large-Scale Differentiable Causal Discovery of Factor Graphs.
CoRR
Romain Lopez, Jan-Christian Hütter, Jonathan K. Pritchard, Aviv Regev
2022 J jnl
Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling.
CoRR
Romain Lopez, Natasa Tagasovska, Stephen Ra, Kyunghyun Cho, Jonathan K. Pritchard, Aviv Regev
2021 — —
Charting Cellular States, One Cell at a Time: Computational, Inferential and Modeling Perspectives.
Romain Lopez
2021 A* conf
Learning from eXtreme Bandit Feedback.
AAAI
Romain Lopez, Inderjit S. Dhillon, Michael I. Jordan
2020 A* conf
Cost-Effective Incentive Allocation via Structured Counterfactual Inference.
AAAI
Romain Lopez, Chenchen Li, Xiang Yan, Junwu Xiong, Michael I. Jordan, Yuan Qi, Le Song
2020 A* conf
Decision-Making with Auto-Encoding Variational Bayes.
NeurIPS
Romain Lopez, Pierre Boyeau, Nir Yosef, Michael I. Jordan, Jeffrey Regier
2020 J jnl
Decision-Making with Auto-Encoding Variational Bayes.
CoRR
Romain Lopez, Pierre Boyeau, Nir Yosef, Michael I. Jordan, Jeffrey Regier
2020 J jnl
Learning from eXtreme Bandit Feedback.
CoRR
Romain Lopez, Inderjit S. Dhillon, Michael I. Jordan
2019 J jnl
A joint model of unpaired data from scRNA-seq and spatial transcriptomics for imputing missing gene expression measurements.
CoRR
Romain Lopez, Achille Nazaret, Maxime Langevin, Jules Samaran, Jeffrey Regier, Michael I. Jordan, Nir Yosef
2019 J jnl
Cost-Effective Incentive Allocation via Structured Counterfactual Inference.
CoRR
Romain Lopez, Chenchen Li, Xiang Yan, Junwu Xiong, Michael I. Jordan, Yuan Qi, Le Song
2018 J jnl
A Deep Generative Model for Semi-Supervised Classification with Noisy Labels.
CoRR
Maxime Langevin, Edouard Mehlman, Jeffrey Regier, Romain Lopez, Michael I. Jordan, Nir Yosef
2018 A* conf
Information Constraints on Auto-Encoding Variational Bayes.
NeurIPS
Romain Lopez, Jeffrey Regier, Michael I. Jordan, Nir Yosef
2018 J jnl
Information Constraints on Auto-Encoding Variational Bayes.
CoRR
Romain Lopez, Jeffrey Regier, Nir Yosef, Michael I. Jordan
2017 J jnl
A deep generative model for gene expression profiles from single-cell RNA sequencing.
CoRR
Romain Lopez, Jeffrey Regier, Michael I. Jordan, Nir Yosef
2013 — conf
Raycast based auto-rigging method for humanoid meshes.
SIGGRAPH Posters
Romain Lopez, Christophe Poirel