Kevin K. Yang

According to our database, Kevin K. Yang authored at least 21 papers between 2017 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

RosettaSearch: Multi-Objective Inference-Time Search for Protein Sequence Design.

Meghana Kshirsagar, Allen Nie, Ching-An Cheng, Fanglei Xue, Rahul Dodhia, Juan M. Lavista Ferres, Kevin K. Yang, Frank DiMaio

CoRR, April, 2026

Trainable subnetworks reveal insights into structure knowledge organization in protein language models.

Ria Vinod, Ava P. Amini, Lorin Crawford, Kevin K. Yang

PLoS Comput. Biol., 2026

2025

Few-shot Protein Fitness Prediction via In-context Learning and Test-time Training.

Felix Teufel, Aaron Kollasch, Yining Huang, Ole Winther, Kevin K. Yang, Pascal Notin, Debora S. Marks

CoRR, December, 2025

MotifBench: A standardized protein design benchmark for motif-scaffolding problems.

Zhuoqi Zheng, Bo Zhang, Kieran Didi, Kevin K. Yang, Jason Yim, Joseph L. Watson, Hai-Feng Chen, Brian L. Trippe

CoRR, February, 2025

Benchmarking uncertainty quantification for protein engineering.

Kevin P. Greenman, Ava P. Amini, Kevin K. Yang

PLoS Comput. Biol., 2025

Tokenized and continuous embedding compressions of protein sequence and structure.

Amy X. Lu, Wilson Yan, Kevin K. Yang, Vladimir Gligorijevic, Kyunghyun Cho, Pieter Abbeel, Richard Bonneau, Nathan C. Frey

Patterns, 2025

ProtNote: a multimodal method for protein-function annotation.

Samir Char, Nathaniel Corley, Sarah Alamdari, Kevin K. Yang, Ava P. Amini

Bioinform., 2025

2024

EnzymeFlow: Generating Reaction-specific Enzyme Catalytic Pockets through Flow Matching and Co-Evolutionary Dynamics.

Chenqing Hua, Yong Liu, Dinghuai Zhang, Odin Zhang, Sitao Luan, Kevin K. Yang, Guy Wolf, Doina Precup, Shuangjia Zheng

CoRR, 2024

Feature Reuse and Scaling: Understanding Transfer Learning with Protein Language Models.

Francesca-Zhoufan Li, Ava P. Amini, Yisong Yue, Kevin K. Yang, Alex Xijie Lu

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Deep self-supervised learning for biosynthetic gene cluster detection and product classification.

Carolina Rios-Martinez, Nicholas Bhattacharya, Ava P. Amini, Lorin Crawford, Kevin K. Yang

PLoS Comput. Biol., 2023

From noise to protein with image models.

Ava P. Amini, Kevin K. Yang

Nat. Comput. Sci., 2023

2022

A topological data analytic approach for discovering biophysical signatures in protein dynamics.

Wai-Shing Tang, Gabriel Monteiro da Silva, Henry Kirveslahti, Erin Skeens, Bibo Feng, Timothy Sudijono, Kevin K. Yang, Sayan Mukherjee, Brenda M. Rubenstein, Lorin Crawford

PLoS Comput. Biol., 2022

Machine learning modeling of family wide enzyme-substrate specificity screens.

Samuel Goldman, Ria Das, Kevin K. Yang, Connor W. Coley

PLoS Comput. Biol., 2022

Protein structure generation via folding diffusion.

Kevin E. Wu, Kevin K. Yang, Rianne van den Berg, James Y. Zou, Alex X. Lu, Ava P. Amini

CoRR, 2022

Exploring evolution-based & -free protein language models as protein function predictors.

Mingyang Hu, Fajie Yuan, Kevin K. Yang, Fusong Ju, Jin Su, Hui Wang, Fei Yang, Qiuyang Ding

CoRR, 2022

2021

Adaptive machine learning for protein engineering.

Brian L. Hie, Kevin K. Yang

CoRR, 2021

Protein sequence design with deep generative models.

Zachary Wu, Kadina E. Johnston, Frances H. Arnold, Kevin K. Yang

CoRR, 2021

FLIP: Benchmark tasks in fitness landscape inference for proteins.

Christian Dallago, Jody Mou, Kadina E. Johnston, Bruce J. Wittmann, Nicholas Bhattacharya, Samuel Goldman, Ali Madani, Kevin K. Yang

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

2019

Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design.

Kevin K. Yang, Yuxin Chen, Alycia Lee, Yisong Yue

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Learned protein embeddings for machine learning.

Kevin K. Yang, Zachary Wu, Claire N. Bedbrook, Frances H. Arnold

Bioinform., 2018

2017

Machine learning to design integral membrane channelrhodopsins for efficient eukaryotic expression and plasma membrane localization.

Claire N. Bedbrook, Kevin K. Yang, Austin J. Rice, Viviana Gradinaru, Frances H. Arnold

PLoS Comput. Biol., 2017