Simon L. Batzner

According to our database, Simon L. Batzner authored at least 12 papers between 2019 and 2023.

Collaborative distances:

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

2023

Biasing energy surfaces towards the unknown.

Simon L. Batzner

Nat. Comput. Sci., 2023

Scaling deep learning for materials discovery.

Amil Merchant, Simon L. Batzner, Samuel S. Schoenholz, Muratahan Aykol, Gowoon Cheon, Ekin Dogus Cubuk

Nat., 2023

Predicting emergence of crystals from amorphous matter with deep learning.

Muratahan Aykol, Amil Merchant, Simon L. Batzner, Jennifer N. Wei, Ekin Dogus Cubuk

CoRR, 2023

Accurate Surface and Finite Temperature Bulk Properties of Lithium Metal at Large Scales using Machine Learning Interaction Potentials.

Mgcini Keith Phuthi, Archie Mingze Yao, Simon L. Batzner, Albert Musaelian, Boris Kozinsky, Ekin Dogus Cubuk, Venkatasubramanian Viswanathan

CoRR, 2023

Scaling the Leading Accuracy of Deep Equivariant Models to Biomolecular Simulations of Realistic Size.

Boris Kozinsky, Albert Musaelian, Anders Johansson, Simon L. Batzner

Proceedings of the International Conference for High Performance Computing, 2023

2022

Fast Uncertainty Estimates in Deep Learning Interatomic Potentials.

Albert Zhu, Simon L. Batzner, Albert Musaelian, Boris Kozinsky

CoRR, 2022

The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials.

Ilyes Batatia, Simon L. Batzner, Dávid Péter Kovács, Albert Musaelian, Gregor N. C. Simm, Ralf Drautz, Christoph Ortner, Boris Kozinsky, Gábor Csányi

CoRR, 2022

Learning Local Equivariant Representations for Large-Scale Atomistic Dynamics.

Albert Musaelian, Simon L. Batzner, Anders Johansson, Lixin Sun, Cameron J. Owen, Mordechai Kornbluth, Boris Kozinsky

CoRR, 2022

2021

SE(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials.

Simon L. Batzner, Tess E. Smidt, Lixin Sun, Jonathan P. Mailoa, Mordechai Kornbluth, Nicola Molinari, Boris Kozinsky

CoRR, 2021

2020

Multitask machine learning of collective variables for enhanced sampling of rare events.

Lixin Sun, Jonathan Vandermause, Simon L. Batzner, Yu Xie, David Clark, Wei Chen, Boris Kozinsky

CoRR, 2020

2019

A fast neural network approach for direct covariant forces prediction in complex multi-element extended systems.

Jonathan P. Mailoa, Mordechai Kornbluth, Simon L. Batzner, Georgy Samsonidze, Stephen T. Lam, Jonathan Vandermause, Chris Ablitt, Nicola Molinari, Boris Kozinsky

Nat. Mach. Intell., 2019

Fast Neural Network Approach for Direct Covariant Forces Prediction in Complex Multi-Element Extended Systems.

Jonathan P. Mailoa, Mordechai Kornbluth, Simon L. Batzner, Georgy Samsonidze, Stephen T. Lam, Chris Ablitt, Nicola Molinari, Boris Kozinsky

CoRR, 2019