Positive-Unlabeled Convolutional Neural Networks for Particle Picking in Cryo-electron Micrographs. - Tristan Bepler; Andrew Morin; Alex J. Noble; Julia Brasch; Lawrence Shapiro; Bonnie Berger (RECOMB, 2018)

Learning protein sequence embeddings using information from structure. - Tristan Bepler; Bonnie Berger (ICLR (Poster), 2019)

Explicitly disentangling image content from translation and rotation with spatial-VAE. - Tristan Bepler; Ellen D. Zhong; Kotaro Kelley; Edward Brignole; Bonnie Berger (NeurIPS, 2019)

Reconstructing continuously heterogeneous structures from single particle cryo-EM with deep generative models. - Ellen D. Zhong; Tristan Bepler; Joseph H. Davis; Bonnie Berger (CoRR, 2019)

Reconstructing continuous distributions of 3D protein structure from cryo-EM images. - Ellen D. Zhong; Tristan Bepler; Joseph H. Davis; Bonnie Berger (ICLR, 2020)

Learning to automate cryo-electron microscopy data collection with Ptolemy. - Paul T. Kim; Alex J. Noble; Anchi Cheng; Tristan Bepler (CoRR, 2021)

Unsupervised Object Representation Learning using Translation and Rotation Group Equivariant VAE. - Alireza Nasiri; Tristan Bepler (NeurIPS, 2022)

Few Shot Protein Generation. - Soumya Ram; Tristan Bepler (CoRR, 2022)

Antibody Representation Learning for Drug Discovery. - Lin Li 005; Esther Gupta; John Spaeth; Leslie Shing; Tristan Bepler; Rajmonda Sulo Caceres (CoRR, 2022)

PoET: A generative model of protein families as sequences-of-sequences. - Timothy F. Truong Jr.; Tristan Bepler (NeurIPS, 2023)