Regev, Aviv

21 publications

AISTATS 2025 Cross-Modality Matching and Prediction of Perturbation Responses with Labeled Gromov-Wasserstein Optimal Transport Jayoung Ryu, Charlotte Bunne, Luca Pinello, Aviv Regev, Romain Lopez

NeurIPS 2025 Derivative-Free Guidance in Continuous and Discrete Diffusion Models with Soft Value-Based Decoding Xiner Li, Yulai Zhao, Chenyu Wang, Gabriele Scalia, Gökcen Eraslan, Surag Nair, Tommaso Biancalani, Shuiwang Ji, Aviv Regev, Sergey Levine, Masatoshi Uehara

ICLR 2025 Fine-Tuning Discrete Diffusion Models via Reward Optimization with Applications to DNA and Protein Design Chenyu Wang, Masatoshi Uehara, Yichun He, Amy Wang, Avantika Lal, Tommi Jaakkola, Sergey Levine, Aviv Regev, Hanchen, Tommaso Biancalani

NeurIPS 2025 Joint‑Embedding vs Reconstruction: Provable Benefits of Latent Space Prediction for Self‑Supervised Learning Hugues Van Assel, Mark Ibrahim, Tommaso Biancalani, Aviv Regev, Randall Balestriero

ICLR 2025 Modeling Complex System Dynamics with Flow Matching Across Time and Conditions Martin Rohbeck, Edward De Brouwer, Charlotte Bunne, Jan-Christian Huetter, Anne Biton, Kelvin Y. Chen, Aviv Regev, Romain Lopez

ICML 2025 Reward-Guided Iterative Refinement in Diffusion Models at Test-Time with Applications to Protein and DNA Design Masatoshi Uehara, Xingyu Su, Yulai Zhao, Xiner Li, Aviv Regev, Shuiwang Ji, Sergey Levine, Tommaso Biancalani

ICLRW 2025 Supervised Contrastive Block Disentanglement Taro Makino, Ji Won Park, Natasa Tagasovska, Takamasa Kudo, Paula Coelho, Heming Yao, Jan-Christian Huetter, Ana Carolina Leote, Burkhard Hoeckendorf, Stephen Ra, David Richmond, Kyunghyun Cho, Aviv Regev, Romain Lopez

ICMLW 2024 Cross-Modality Matching and Prediction of Perturbation Responses with Labeled Gromov-Wasserstein Optimal Transport Jayoung Ryu, Romain Lopez, Charlotte Bunne, Luca Pinello, Aviv Regev

ICMLW 2024 Cross-Modality Matching and Prediction of Perturbation Responses with Labeled Gromov-Wasserstein Optimal Transport Jayoung Ryu, Romain Lopez, Charlotte Bunne, Luca Pinello, Aviv Regev

NeurIPSW 2024 Derivative-Free Guidance in Continuous and Discrete Diffusion Models with Soft Value-Based Decoding Xiner Li, Yulai Zhao, Chenyu Wang, Gabriele Scalia, Gökcen Eraslan, Surag Nair, Tommaso Biancalani, Shuiwang Ji, Aviv Regev, Sergey Levine, Masatoshi Uehara

NeurIPSW 2024 Fine-Tuning Discrete Diffusion Models via Reward Optimization with Applications to DNA and Protein Design Chenyu Wang, Masatoshi Uehara, Yichun He, Amy Wang, Tommaso Biancalani, Avantika Lal, Tommi Jaakkola, Sergey Levine, Hanchen, Aviv Regev

NeurIPSW 2024 Learning Multi-Cellular Representations of Single-Cell Transcriptomics Data Enables Characterization of Patient-Level Disease States Tianyu Liu, Edward De Brouwer, Tony Kuo, Nathaniel Lee Diamant, Missarova Alsu, Minsheng Hao, Hanchen, Hector Corrada Bravo, Gabriele Scalia, Aviv Regev, Graham Heimberg

NeurIPSW 2024 Modeling Complex System Dynamics with Flow Matching Across Time and Conditions Martin Rohbeck, Charlotte Bunne, Edward De Brouwer, Jan-Christian Huetter, Anne Biton, Kelvin Y. Chen, Aviv Regev, Romain Lopez

ICLRW 2024 Multi-ContrastiveVAE Disentangles Perturbation Effects in Single Cell Images from Optical Pooled Screens Zitong Jerry Wang, Romain Lopez, Jan-Christian Huetter, Takamasa Kudo, Heming Yao, Philipp Hanslovsky, Burkhard Hoeckendorf, Rahul Ram Mohan, David Richmond, Aviv Regev

CLeaR 2024 Toward the Identifiability of Comparative Deep Generative Models Romain Lopez, Jan-Christian Huetter, Ehsan Hajiramezanali, Jonathan K Pritchard, Aviv Regev

CLeaR 2023 Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling Romain Lopez, Natasa Tagasovska, Stephen Ra, Kyunghyun Cho, Jonathan Pritchard, Aviv Regev

NeurIPS 2022 Large-Scale Differentiable Causal Discovery of Factor Graphs Romain Lopez, Jan-Christian Huetter, Jonathan Pritchard, Aviv Regev

NeurIPSW 2022 Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling Romain Lopez, Natasa Tagasovska, Stephen Ra, Kyunghyun Cho, Jonathan Pritchard, Aviv Regev

JMLR 2006 MinReg: A Scalable Algorithm for Learning Parsimonious Regulatory Networks in Yeast and Mammals Dana Pe'er, Amos Tanay, Aviv Regev

JMLR 2005 Learning Module Networks Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller, Nir Friedman

UAI 2003 Learning Module Networks Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller, Nir Friedman