Ra, Stephen

17 publications

ICLRW 2025 Orchestrating Tool Ecosystem of Drug Discovery with Intention-Aware LLM Agents Mingyu Derek Ma, Karina Zadorozhny, Jesse Swanson, Nathan C. Frey, Keunwoo Choi, Maksim Eremeev, Sabrina J Mielke, Wenmo Sun, Melody Liu, Jonathan Wickes, Vladimir Gligorijevic, Richard Bonneau, Henri Dwyer, Kyunghyun Cho, Stephen Ra

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

ICML 2024 BOtied: Multi-Objective Bayesian Optimization with Tied Multivariate Ranks Ji Won Park, Natasa Tagasovska, Michael Maser, Stephen Ra, Kyunghyun Cho

TMLR 2024 Blind Biological Sequence Denoising with Self-Supervised Set Learning Nathan Hoyen Ng, Ji Won Park, Jae Hyeon Lee, Ryan Lewis Kelly, Stephen Ra, Kyunghyun Cho

ICLR 2024 Concept Bottleneck Generative Models Aya Abdelsalam Ismail, Julius Adebayo, Hector Corrada Bravo, Stephen Ra, Kyunghyun Cho

ICLR 2024 Protein Discovery with Discrete Walk-Jump Sampling Nathan C. Frey, Dan Berenberg, Karina Zadorozhny, Joseph Kleinhenz, Julien Lafrance-Vanasse, Isidro Hotzel, Yan Wu, Stephen Ra, Richard Bonneau, Kyunghyun Cho, Andreas Loukas, Vladimir Gligorijevic, Saeed Saremi

NeurIPS 2023 3D Molecule Generation by Denoising Voxel Grids Pedro O O. Pinheiro, Joshua Rackers, Joseph Kleinhenz, Michael Maser, Omar Mahmood, Andrew Watkins, Stephen Ra, Vishnu Sresht, Saeed Saremi

ICMLW 2023 Concept Bottleneck Generative Models Aya Abdelsalam Ismail, Julius Adebayo, Hector Corrada Bravo, Stephen Ra, Kyunghyun Cho

NeurIPSW 2023 Identifying Regularization Schemes That Make Feature Attributions Faithful Julius Adebayo, Samuel Don Stanton, Simon Kelow, Michael Maser, Richard Bonneau, Vladimir Gligorijevic, Kyunghyun Cho, Stephen Ra, Nathan C. Frey

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

ICLRW 2023 Learning Protein Family Manifolds with Smoothed Energy-Based Models Nathan C. Frey, Dan Berenberg, Joseph Kleinhenz, Isidro Hotzel, Julien Lafrance-Vanasse, Ryan Lewis Kelly, Yan Wu, Arvind Rajpal, Stephen Ra, Richard Bonneau, Kyunghyun Cho, Andreas Loukas, Vladimir Gligorijevic, Saeed Saremi

NeurIPS 2023 OpenProteinSet: Training Data for Structural Biology at Scale Gustaf Ahdritz, Nazim Bouatta, Sachin Kadyan, Lukas Jarosch, Dan Berenberg, Ian Fisk, Andrew Watkins, Stephen Ra, Richard Bonneau, Mohammed AlQuraishi

NeurIPSW 2023 Protein Discovery with Discrete Walk-Jump Sampling Nathan Frey, Dan Berenberg, Karina Zadorozhny, Joseph Kleinhenz, Julien Lafrance-Vanasse, Isidro Hotzel, Yan Wu, Stephen Ra, Richard Bonneau, Kyunghyun Cho, Vladimir Gligorijevic, Saeed Saremi

NeurIPSW 2022 A Pareto-Optimal Compositional Energy-Based Model for Sampling and Optimization of Protein Sequences Natasa Tagasovska, Nathan C. Frey, Andreas Loukas, Isidro Hotzel, Julien Lafrance-Vanasse, Ryan Lewis Kelly, Yan Wu, Arvind Rajpal, Richard Bonneau, Kyunghyun Cho, Stephen Ra, Vladimir Gligorijevic

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

ICLRW 2022 Multi-Segment Preserving Sampling for Deep Manifold Sampler Dan Berenberg, Jae Hyeon Lee, Simon Kelow, Ji Won Park, Andrew Watkins, Richard Bonneau, Vladimir Gligorijevic, Stephen Ra, Kyunghyun Cho

NeurIPSW 2022 PropertyDAG: Multi-Objective Bayesian Optimization of Partially Ordered, Mixed-Variable Properties for Biological Sequence Design Ji Won Park, Samuel Don Stanton, Saeed Saremi, Andrew Martin Watkins, Henri Dwyer, Vladimir Gligorijevic, Richard Bonneau, Stephen Ra, Kyunghyun Cho