Kuang, Yilun

9 publications

ICLR 2025 Bayesian Optimization of Antibodies Informed by a Generative Model of Evolving Sequences Alan Nawzad Amin, Nate Gruver, Yilun Kuang, Yucen Lily Li, Hunter Elliott, Calvin McCarter, Aniruddh Raghu, Peyton Greenside, Andrew Gordon Wilson

ICML 2025 Customizing the Inductive Biases of SoftMax Attention Using Structured Matrices Yilun Kuang, Noah Amsel, Sanae Lotfi, Shikai Qiu, Andres Potapczynski, Andrew Gordon Wilson

NeurIPSW 2024 Bayesian Optimization of Antibodies Informed by a Generative Model of Evolving Sequences Alan Nawzad Amin, Nate Gruver, Yucen Lily Li, Yilun Kuang, Hunter Elliott, Calvin McCarter, Aniruddh Raghu, Peyton Greenside, Andrew Gordon Wilson

ICML 2024 Non-Vacuous Generalization Bounds for Large Language Models Sanae Lotfi, Marc Anton Finzi, Yilun Kuang, Tim G. J. Rudner, Micah Goldblum, Andrew Gordon Wilson

NeurIPS 2024 Unlocking Tokens as Data Points for Generalization Bounds on Larger Language Models Sanae Lotfi, Yilun Kuang, Brandon Amos, Micah Goldblum, Marc Finzi, Andrew Gordon Wilson

ICMLW 2024 Unlocking Tokens as Data Points for Generalization Bounds on Larger Language Models Sanae Lotfi, Yilun Kuang, Marc Anton Finzi, Brandon Amos, Micah Goldblum, Andrew Gordon Wilson

NeurIPS 2023 Learning Efficient Coding of Natural Images with Maximum Manifold Capacity Representations Thomas Yerxa, Yilun Kuang, Eero P. Simoncelli, SueYeon Chung

NeurIPSW 2023 Non-Vacuous Generalization Bounds for Large Language Models Sanae Lotfi, Marc Finzi, Yilun Kuang, Tim Rudner, Micah Goldblum, Andrew Wilson

NeurIPSW 2023 Unsupervised Learning on Spontaneous Retinal Activity Leads to Efficient Neural Representation Geometry Andrew Ligeralde, Yilun Kuang, Thomas Edward Yerxa, Miah N Pitcher, Marla Feller, SueYeon Chung