Tristan Bepler

According to our database, Tristan Bepler authored at least 10 papers between 2018 and 2023.

Collaborative distances:

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

2023

PoET: A generative model of protein families as sequences-of-sequences.

Timothy F. Truong Jr., Tristan Bepler

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Antibody Representation Learning for Drug Discovery.

Lin Li, Esther Gupta, John Spaeth, Leslie Shing, Tristan Bepler, Rajmonda Sulo Caceres

CoRR, 2022

Few Shot Protein Generation.

Soumya Ram, Tristan Bepler

CoRR, 2022

Unsupervised Object Representation Learning using Translation and Rotation Group Equivariant VAE.

Alireza Nasiri, Tristan Bepler

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Learning to automate cryo-electron microscopy data collection with Ptolemy.

Paul T. Kim, Alex J. Noble, Anchi Cheng, Tristan Bepler

CoRR, 2021

2020

Reconstructing continuous distributions of 3D protein structure from cryo-EM images.

Ellen D. Zhong, Tristan Bepler, Joseph H. Davis, Bonnie Berger

Proceedings of the 8th International Conference on Learning Representations, 2020

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

Explicitly disentangling image content from translation and rotation with spatial-VAE.

Tristan Bepler, Ellen D. Zhong, Kotaro Kelley, Edward Brignole, Bonnie Berger

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning protein sequence embeddings using information from structure.

Tristan Bepler, Bonnie Berger

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

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

Proceedings of the Research in Computational Molecular Biology, 2018