Stephen Ra

21 papers A* 5Journal 15Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
TwinWeaver: An LLM-Based Foundation Model Framework for Pan-Cancer Digital Twins.
CoRR
Nikita Makarov, Maria Bordukova, Lena Voith von Voithenberg, Estrella Pivel-Villanueva, Sabrina Mielke, Jonathan Wickes, Hanchen Wang, Mingyu Derek Ma, Keunwoo Choi, Kyunghyun Cho, Stephen Ra, Raul Rodriguez-Esteban, Fabian Schmich, Michael P. Menden
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 J jnl
Antibody DomainBed: Out-of-Distribution Generalization in Therapeutic Protein Design.
CoRR
Natasa Tagasovska, Ji Won Park, Matthieu Kirchmeyer, Nathan C. Frey, Andrew Martin Watkins, Aya Abdelsalam Ismail, Arian Rokkum Jamasb, Edith Lee, Tyler Bryson, Stephen Ra, Kyunghyun Cho
2024 A* conf
BOtied: Multi-objective Bayesian optimization with tied multivariate ranks.
ICML
Ji Won Park, Natasa Tagasovska, Michael Maser, Stephen Ra, Kyunghyun Cho
2024 J jnl
Blind Biological Sequence Denoising with Self-Supervised Set Learning.
Trans. Mach. Learn. Res.
Nathan H. Ng, Ji Won Park, Jae Hyeon Lee, Ryan Lewis Kelly, Stephen Ra, Kyunghyun Cho
2024 A* conf
Concept Bottleneck Generative Models.
ICLR
Aya Abdelsalam Ismail, Julius Adebayo, Héctor Corrada Bravo, Stephen Ra, Kyunghyun Cho
2024 A* conf
Protein Discovery with Discrete Walk-Jump Sampling.
ICLR
Nathan C. Frey, Daniel Berenberg, Karina Zadorozhny, Joseph Kleinhenz, Julien Lafrance-Vanasse, Isidro Hötzel, Yan Wu, Stephen Ra, Richard Bonneau, Kyunghyun Cho, Andreas Loukas, Vladimir Gligorijevic, Saeed Saremi
2023 A* conf
3D molecule generation by denoising voxel grids.
NeurIPS
Pedro O. Pinheiro, Joshua A. Rackers, Joseph Kleinhenz, Michael Maser, Omar Mahmood, Andrew M. Watkins, Stephen Ra, Vishnu Sresht, Saeed Saremi
2023 J jnl
3D molecule generation by denoising voxel grids.
CoRR
Pedro O. Pinheiro, Joshua A. Rackers, Joseph Kleinhenz, Michael Maser, Omar Mahmood, Andrew Martin Watkins, Stephen Ra, Vishnu Sresht, Saeed Saremi
2023 J jnl
BOtied: Multi-objective Bayesian optimization with tied multivariate ranks.
CoRR
Ji Won Park, Natasa Tagasovska, Michael Maser, Stephen Ra, Kyunghyun Cho
2023 J jnl
Blind Biological Sequence Denoising with Self-Supervised Set Learning.
CoRR
Nathan Ng, Ji Won Park, Jae Hyeon Lee, Ryan Lewis Kelly, Stephen Ra, Kyunghyun Cho
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
OpenProteinSet: Training data for structural biology at scale.
NeurIPS
Gustaf Ahdritz, Nazim Bouatta, Sachin Kadyan, Lukas Jarosch, Daniel Berenberg, Ian Fisk, Andrew M. Watkins, Stephen Ra, Richard Bonneau, Mohammed AlQuraishi
2023 J jnl
OpenProteinSet: Training data for structural biology at scale.
CoRR
Gustaf Ahdritz, Nazim Bouatta, Sachin Kadyan, Lukas Jarosch, Daniel Berenberg, Ian Fisk, Andrew M. Watkins, Stephen Ra, Richard Bonneau, Mohammed AlQuraishi
2023 J jnl
Protein Discovery with Discrete Walk-Jump Sampling.
CoRR
Nathan C. Frey, Daniel Berenberg, Karina Zadorozhny, Joseph Kleinhenz, Julien Lafrance-Vanasse, Isidro Hötzel, Yan Wu, Stephen Ra, Richard Bonneau, Kyunghyun Cho, Andreas Loukas, Vladimir Gligorijevic, Saeed Saremi
2022 J jnl
A Pareto-optimal compositional energy-based model for sampling and optimization of protein sequences.
CoRR
Natasa Tagasovska, Nathan C. Frey, Andreas Loukas, Isidro Hötzel, Julien Lafrance-Vanasse, Ryan Lewis Kelly, Yan Wu, Arvind Rajpal, Richard Bonneau, Kyunghyun Cho, Stephen Ra, Vladimir Gligorijevic
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
2022 J jnl
Multi-segment preserving sampling for deep manifold sampler.
CoRR
Daniel Berenberg, Jae Hyeon Lee, Simon Kelow, Ji Won Park, Andrew M. Watkins, Vladimir Gligorijevic, Richard Bonneau, Stephen Ra, Kyunghyun Cho
2022 J jnl
PropertyDAG: Multi-objective Bayesian optimization of partially ordered, mixed-variable properties for biological sequence design.
CoRR
Ji Won Park, Samuel Stanton, Saeed Saremi, Andrew M. Watkins, Henri Dwyer, Vladimir Gligorijevic, Richard Bonneau, Stephen Ra, Kyunghyun Cho
2020 J jnl
Standard machine learning approaches outperform deep representation learning on phenotype prediction from transcriptomics data.
BMC Bioinform.
Aaron M. Smith, Jonathan R. Walsh, John Long, Craig B. Davis, Peter Henstock, Martin R. Hodge, Mateusz Maciejewski, Xinmeng Jasmine Mu, Stephen Ra, Shanrong Zhao, Daniel Ziemek, Charles K. Fisher
2019 J jnl
Black Box Recursive Translations for Molecular Optimization.
CoRR
Farhan N. Damani, Vishnu Sresht, Stephen Ra