Jonathan Godwin

Publication Activity (10 Years)

Years Active: 2016-2023
Publications (10 Years): 14

Top Topics

Inference In Graphical Models

Supervised Learning

Graph Representation

Top Venues

Publications

Sheheryar Zaidi, Michael Schaarschmidt, James Martens, Hyunjik Kim, Yee Whye Teh, Alvaro Sanchez-Gonzalez, Peter W. Battaglia, Razvan Pascanu, Jonathan Godwin
Pre-training via Denoising for Molecular Property Prediction. ICLR (2023)
Tim Bechtel, Daniel T. Speckhard, Jonathan Godwin, Claudia Draxl
Band-gap regression with architecture-optimized message-passing neural networks. CoRR (2023)
Sheheryar Zaidi, Michael Schaarschmidt, James Martens, Hyunjik Kim, Yee Whye Teh, Alvaro Sanchez-Gonzalez, Peter W. Battaglia, Razvan Pascanu, Jonathan Godwin
Pre-training via Denoising for Molecular Property Prediction. CoRR (2022)
Michael Schaarschmidt, Morgane Riviere, Alex M. Ganose, James S. Spencer, Alexander L. Gaunt, James Kirkpatrick, Simon Axelrod, Peter W. Battaglia, Jonathan Godwin
Learned Force Fields Are Ready For Ground State Catalyst Discovery. CoRR (2022)
Kimberly Stachenfeld, Drummond Buschman Fielding, Dmitrii Kochkov, Miles D. Cranmer, Tobias Pfaff, Jonathan Godwin, Can Cui, Shirley Ho, Peter W. Battaglia, Alvaro Sanchez-Gonzalez
Learned Simulators for Turbulence. ICLR (2022)
Jonathan Godwin, Michael Schaarschmidt, Alexander L. Gaunt, Alvaro Sanchez-Gonzalez, Yulia Rubanova, Petar Velickovic, James Kirkpatrick, Peter W. Battaglia
Simple GNN Regularisation for 3D Molecular Property Prediction and Beyond. ICLR (2022)
Ravichandra Addanki, Peter W. Battaglia, David Budden, Andreea Deac, Jonathan Godwin, Thomas Keck, Wai Lok Sibon Li, Alvaro Sanchez-Gonzalez, Jacklynn Stott, Shantanu Thakoor, Petar Velickovic
Large-scale graph representation learning with very deep GNNs and self-supervision. CoRR (2021)
Jonathan Godwin, Michael Schaarschmidt, Alexander Gaunt, Alvaro Sanchez-Gonzalez, Yulia Rubanova, Petar Velickovic, James Kirkpatrick, Peter W. Battaglia
Very Deep Graph Neural Networks Via Noise Regularisation. CoRR (2021)
Kimberly L. Stachenfeld, Drummond B. Fielding, Dmitrii Kochkov, Miles D. Cranmer, Tobias Pfaff, Jonathan Godwin, Can Cui, Shirley Ho, Peter W. Battaglia, Alvaro Sanchez-Gonzalez
Learned Coarse Models for Efficient Turbulence Simulation. CoRR (2021)
Michael Schaarschmidt, Dominik Grewe, Dimitrios Vytiniotis, Adam Paszke, Georg Stefan Schmid, Tamara Norman, James Molloy, Jonathan Godwin, Norman Alexander Rink, Vinod Nair, Dan Belov
Automap: Towards Ergonomic Automated Parallelism for ML Models. CoRR (2021)
Kimberly L. Stachenfeld, Jonathan Godwin, Peter W. Battaglia
Graph Networks with Spectral Message Passing. CoRR (2021)
Alvaro Sanchez-Gonzalez, Jonathan Godwin, Tobias Pfaff, Rex Ying, Jure Leskovec, Peter W. Battaglia
Learning to Simulate Complex Physics with Graph Networks. CoRR (2020)
Alvaro Sanchez-Gonzalez, Jonathan Godwin, Tobias Pfaff, Rex Ying, Jure Leskovec, Peter W. Battaglia
Learning to Simulate Complex Physics with Graph Networks. ICML (2020)
Jonathan Godwin, Pontus Stenetorp, Sebastian Riedel
Deep Semi-Supervised Learning with Linguistically Motivated Sequence Labeling Task Hierarchies. CoRR (2016)