Peyton Greenside

According to our database, Peyton Greenside authored at least 8 papers between 2016 and 2023.

Collaborative distances:

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

2023

Inverse Protein Folding Using Deep Bayesian Optimization.

Natalie Maus, Yimeng Zeng, Daniel Allen Anderson, Phillip M. Maffettone, Aaron Solomon, Peyton Greenside, Osbert Bastani, Jacob R. Gardner

CoRR, 2023

2022

Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders.

Samuel Stanton, Wesley J. Maddox, Nate Gruver, Phillip M. Maffettone, Emily Delaney, Peyton Greenside, Andrew Gordon Wilson

Proceedings of the International Conference on Machine Learning, 2022

2020

A Hierarchical Approach to Scaling Batch Active Search Over Structured Data.

Vivek Myers, Peyton Greenside

CoRR, 2020

2019

CrowdVariant: a crowdsourcing approach to classify copy number variants.

Peyton Greenside, Justin M. Zook, Marc Salit, Madeleine L. Cule, Ryan Poplin, Mark A. DePristo

Proceedings of the Biocomputing 2019: Proceedings of the Pacific Symposium, 2019

2018

Discovering epistatic feature interactions from neural network models of regulatory DNA sequences.

Peyton Greenside, Tyler Shimko, Polly Fordyce, Anshul Kundaje

Bioinform., 2018

Prediction of protein-ligand interactions from paired protein sequence motifs and ligand substructures.

Peyton Greenside, Maureen Hillenmeyer, Anshul Kundaje

Proceedings of the Biocomputing 2018: Proceedings of the Pacific Symposium, 2018

2017

Learning Important Features Through Propagating Activation Differences.

Avanti Shrikumar, Peyton Greenside, Anshul Kundaje

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Not Just a Black Box: Learning Important Features Through Propagating Activation Differences.

Avanti Shrikumar, Peyton Greenside, Anna Shcherbina, Anshul Kundaje

CoRR, 2016