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Journal Articles
- 2023
[j3]Amil Merchant
, Simon L. Batzner, Samuel S. Schoenholz, Muratahan Aykol, Gowoon Cheon, Ekin Dogus Cubuk:
Scaling deep learning for materials discovery. Nat. 624(7990): 80-85 (2023)- [j2]Simon L. Batzner:
Biasing energy surfaces towards the unknown. Nat. Comput. Sci. 3(3): 190-191 (2023) - 2019
- [j1]Jonathan P. Mailoa, Mordechai Kornbluth, Simon L. Batzner, Georgy Samsonidze, Stephen T. Lam, Jonathan Vandermause, Chris Ablitt, Nicola Molinari, Boris Kozinsky:
A fast neural network approach for direct covariant forces prediction in complex multi-element extended systems. Nat. Mach. Intell. 1(10): 471-479 (2019)
Conference and Workshop Papers
- 2023
- [c1]Boris Kozinsky, Albert Musaelian, Anders Johansson, Simon L. Batzner:
Scaling the Leading Accuracy of Deep Equivariant Models to Biomolecular Simulations of Realistic Size. SC 2023: 2:1-2:12
Informal and Other Publications
- 2024
- [i10]Sherry Yang, Simon L. Batzner, Ruiqi Gao, Muratahan Aykol, Alexander L. Gaunt, Brendan McMorrow, Danilo J. Rezende, Dale Schuurmans, Igor Mordatch, Ekin D. Cubuk:
Generative Hierarchical Materials Search. CoRR abs/2409.06762 (2024) - 2023
- [i9]Albert Musaelian, Anders Johansson, Simon L. Batzner, Boris Kozinsky:
Scaling the leading accuracy of deep equivariant models to biomolecular simulations of realistic size. CoRR abs/2304.10061 (2023) - [i8]Mgcini Keith Phuthi, Archie Mingze Yao, Simon L. Batzner, Albert Musaelian, Boris Kozinsky, Ekin Dogus Cubuk, Venkatasubramanian Viswanathan:
Accurate Surface and Finite Temperature Bulk Properties of Lithium Metal at Large Scales using Machine Learning Interaction Potentials. CoRR abs/2305.06925 (2023) - [i7]Muratahan Aykol, Amil Merchant, Simon L. Batzner, Jennifer N. Wei, Ekin Dogus Cubuk:
Predicting emergence of crystals from amorphous matter with deep learning. CoRR abs/2310.01117 (2023) - 2022
- [i6]Albert Musaelian, Simon L. Batzner, Anders Johansson, Lixin Sun, Cameron J. Owen, Mordechai Kornbluth, Boris Kozinsky:
Learning Local Equivariant Representations for Large-Scale Atomistic Dynamics. CoRR abs/2204.05249 (2022) - [i5]Ilyes Batatia, Simon L. Batzner, Dávid Péter Kovács, Albert Musaelian, Gregor N. C. Simm, Ralf Drautz, Christoph Ortner, Boris Kozinsky, Gábor Csányi:
The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials. CoRR abs/2205.06643 (2022) - [i4]Albert Zhu, Simon L. Batzner, Albert Musaelian, Boris Kozinsky:
Fast Uncertainty Estimates in Deep Learning Interatomic Potentials. CoRR abs/2211.09866 (2022) - 2021
- [i3]Simon L. Batzner, Tess E. Smidt, Lixin Sun, Jonathan P. Mailoa, Mordechai Kornbluth, Nicola Molinari, Boris Kozinsky:
SE(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials. CoRR abs/2101.03164 (2021) - 2020
- [i2]Lixin Sun, Jonathan Vandermause, Simon L. Batzner, Yu Xie, David Clark, Wei Chen, Boris Kozinsky:
Multitask machine learning of collective variables for enhanced sampling of rare events. CoRR abs/2012.03909 (2020) - 2019
- [i1]Jonathan P. Mailoa, Mordechai Kornbluth, Simon L. Batzner, Georgy Samsonidze, Stephen T. Lam, Chris Ablitt, Nicola Molinari, Boris Kozinsky:
Fast Neural Network Approach for Direct Covariant Forces Prediction in Complex Multi-Element Extended Systems. CoRR abs/1905.02791 (2019)
Coauthor Index
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