Nathan C. Frey

According to our database, Nathan C. Frey authored at least 19 papers between 2021 and 2023.

Collaborative distances:

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

2023

Neural scaling of deep chemical models.

Nathan C. Frey, Ryan Soklaski, Simon Axelrod, Siddharth Samsi, Rafael Gómez-Bombarelli, Connor W. Coley, Vijay Gadepally

Nat. Mac. Intell., October, 2023

Protein Discovery with Discrete Walk-Jump Sampling.

Nathan C. Frey, Daniel Berenberg, Karina Zadorozhny, Joseph Kleinhenz, Julien Lafrance-Vanasse, Isidro Hötzel, Yan Wu, Stephen Ra, Richard Bonneau, Kyunghyun Cho, Andreas Loukas, Vladimir Gligorijevic, Saeed Saremi

CoRR, 2023

SupSiam: Non-contrastive Auxiliary Loss for Learning from Molecular Conformers.

Michael Maser, Ji Won Park, Joshua Yao-Yu Lin, Jae Hyeon Lee, Nathan C. Frey, Andrew M. Watkins

CoRR, 2023

Protein Design with Guided Discrete Diffusion.

Nate Gruver, Samuel Stanton, Nathan C. Frey, Tim G. J. Rudner, Isidro Hötzel, Julien Lafrance-Vanasse, Arvind Rajpal, Kyunghyun Cho, Andrew Gordon Wilson

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

2022

SELFIES and the future of molecular string representations.

Mario Krenn, Qianxiang Ai, Senja Barthel, Nessa Carson, Angelo Frei, Nathan C. Frey, Pascal Friederich, Théophile Gaudin, Alberto Alexander Gayle, Kevin Maik Jablonka, Rafael F. Lameiro, Dominik Lemm, Alston Lo, Seyed Mohamad Moosavi, José Manuel Nápoles-Duarte, AkshatKumar Nigam, Robert Pollice, Kohulan Rajan, Ulrich Schatzschneider, Philippe Schwaller, Marta Skreta, Berend Smit, Felix Strieth-Kalthoff, Chong Sun, Gary Tom, Guido Falk von Rudorff, Andrew Wang, Andrew D. White, Adamo Young, Rose Yu, Alán Aspuru-Guzik

Patterns, 2022

Roughness of Molecular Property Landscapes and Its Impact on Modellability.

Matteo Aldeghi, David E. Graff, Nathan C. Frey, Joseph A. Morrone, Edward O. Pyzer-Knapp, Kirk E. Jordan, Connor W. Coley

J. Chem. Inf. Model., 2022

Graph Contrastive Learning for Materials.

Teddy Koker, Keegan Quigley, Will Spaeth, Nathan C. Frey, Lin Li

CoRR, 2022

A Pareto-optimal compositional energy-based model for sampling and optimization of protein sequences.

Natasa Tagasovska, Nathan C. Frey, Andreas Loukas, Isidro Hötzel, Julien Lafrance-Vanasse, Ryan Lewis Kelly, Yan Wu, Arvind Rajpal, Richard Bonneau, Kyunghyun Cho, Stephen Ra, Vladimir Gligorijevic

CoRR, 2022

The MIT Supercloud Workload Classification Challenge.

Benny J. Tang, Qiqi Chen, Matthew L. Weiss, Nathan C. Frey, Joseph McDonald, David Bestor, Charles Yee, William Arcand, Chansup Byun, Daniel Edelman, Matthew Hubbell, Michael Jones, Jeremy Kepner, Anna Klein, Adam Michaleas, Peter Michaleas, Lauren Milechin, Julia S. Mullen, Andrew Prout, Albert Reuther, Antonio Rosa, Andrew Bowne, Lindsey McEvoy, Baolin Li, Devesh Tiwari, Vijay Gadepally, Siddharth Samsi

CoRR, 2022

FastFlows: Flow-Based Models for Molecular Graph Generation.

Nathan C. Frey, Vijay Gadepally, Bharath Ramsundar

CoRR, 2022

Great Power, Great Responsibility: Recommendations for Reducing Energy for Training Language Models.

Joseph McDonald, Baolin Li, Nathan C. Frey, Devesh Tiwari, Vijay Gadepally, Siddharth Samsi

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022

A Green(er) World for A.I.

Dan Zhao, Nathan C. Frey, Joseph McDonald, Matthew Hubbell, David Bestor, Michael Jones, Andrew Prout, Vijay Gadepally, Siddharth Samsi

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2022

Loss Curve Approximations for Fast Neural Architecture Ranking & Training Elasticity Estimation.

Dan Zhao, Nathan C. Frey, Vijay Gadepally, Siddharth Samsi

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2022

The MIT Supercloud Workload Classification Challenge.

Benny J. Tang, Qiqi Chen, Matthew L. Weiss, Nathan C. Frey, Joseph McDonald, David Bestor, Charles Yee, William Arcand, William Bergeron, Chansup Byun, Daniel Edelman, Michael Houle, Matthew Hubbell, Michael Jones, Jeremy Kepner, Anna Klein, Adam Michaleas, Peter Michaleas, Lauren Milechin, Julia S. Mullen, Andrew Prout, Albert Reuther, Antonio Rosa, Andrew Bowne, Lindsey McEvoy, Baolin Li, Devesh Tiwari, Vijay Gadepally, Siddharth Samsi

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2022

Energy-aware neural architecture selection and hyperparameter optimization.

Nathan C. Frey, Dan Zhao, Simon Axelrod, Michael Jones, David Bestor, Vijay Gadepally, Rafael Gómez-Bombarelli, Siddharth Samsi

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2022

Benchmarking Resource Usage for Efficient Distributed Deep Learning.

Nathan C. Frey, Baolin Li, Joseph McDonald, Dan Zhao, Michael Jones, David Bestor, Devesh Tiwari, Vijay Gadepally, Siddharth Samsi

Proceedings of the IEEE High Performance Extreme Computing Conference, 2022

2021

Bringing Atomistic Deep Learning to Prime Time.

Nathan C. Frey, Siddharth Samsi, Bharath Ramsundar, Connor W. Coley, Vijay Gadepally

CoRR, 2021

Scalable Geometric Deep Learning on Molecular Graphs.

Nathan C. Frey, Siddharth Samsi, Joseph McDonald, Lin Li, Connor W. Coley, Vijay Gadepally

CoRR, 2021

The Pseudo Projection Operator: Applications of Deep Learning to Projection Based Filtering in Non-Trivial Frequency Regimes.

Matthew L. Weiss, Nathan C. Frey, Siddharth Samsi, Randy C. Paffenroth, Vijay Gadepally

CoRR, 2021