Simon L. Batzner

17 papers A* 1A 1Journal 15

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Predicting emergence of crystals from amorphous precursors with deep learning potentials. Nat. Comput. Sci. Muratahan Aykol, Amil Merchant, Simon L. Batzner, Jennifer N. Wei, Ekin Dogus Cubuk
2025	J	`jnl`	The design space of E(3)-equivariant atom-centred interatomic potentials. Nat. Mac. Intell. Ilyes Batatia, Simon L. Batzner, Dávid Péter Kovács, Albert Musaelian, Gregor N. C. Simm, Ralf Drautz, Christoph Ortner, Boris Kozinsky, Gábor Csányi
2024	A*	`conf`	Generative Hierarchical Materials Search. NeurIPS Sherry Yang, Simon L. Batzner, Ruiqi Gao, Muratahan Aykol, Alexander L. Gaunt, Brendan McMorrow, Danilo Jimenez Rezende, Dale Schuurmans, Igor Mordatch, Ekin Dogus Cubuk
2024	J	`jnl`	Generative Hierarchical Materials Search. CoRR Sherry Yang, Simon L. Batzner, Ruiqi Gao, Muratahan Aykol, Alexander L. Gaunt, Brendan McMorrow, Danilo J. Rezende, Dale Schuurmans, Igor Mordatch, Ekin D. Cubuk
2023	J	`jnl`	Accurate Surface and Finite Temperature Bulk Properties of Lithium Metal at Large Scales using Machine Learning Interaction Potentials. CoRR Mgcini Keith Phuthi, Archie Mingze Yao, Simon L. Batzner, Albert Musaelian, Boris Kozinsky, Ekin Dogus Cubuk, Venkatasubramanian Viswanathan
2023	J	`jnl`	Biasing energy surfaces towards the unknown. Nat. Comput. Sci. Simon L. Batzner
2023	J	`jnl`	Predicting emergence of crystals from amorphous matter with deep learning. CoRR Muratahan Aykol, Amil Merchant, Simon L. Batzner, Jennifer N. Wei, Ekin Dogus Cubuk
2023	J	`jnl`	Scaling deep learning for materials discovery. Nat. Amil Merchant, Simon L. Batzner, Samuel S. Schoenholz, Muratahan Aykol, Gowoon Cheon, Ekin Dogus Cubuk
2023	A	`conf`	Scaling the Leading Accuracy of Deep Equivariant Models to Biomolecular Simulations of Realistic Size. SC Boris Kozinsky, Albert Musaelian, Anders Johansson, Simon L. Batzner
2023	J	`jnl`	Scaling the leading accuracy of deep equivariant models to biomolecular simulations of realistic size. CoRR Albert Musaelian, Anders Johansson, Simon L. Batzner, Boris Kozinsky
2022	J	`jnl`	Fast Uncertainty Estimates in Deep Learning Interatomic Potentials. CoRR Albert Zhu, Simon L. Batzner, Albert Musaelian, Boris Kozinsky
2022	J	`jnl`	Learning Local Equivariant Representations for Large-Scale Atomistic Dynamics. CoRR Albert Musaelian, Simon L. Batzner, Anders Johansson, Lixin Sun, Cameron J. Owen, Mordechai Kornbluth, Boris Kozinsky
2022	J	`jnl`	The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials. CoRR Ilyes Batatia, Simon L. Batzner, Dávid Péter Kovács, Albert Musaelian, Gregor N. C. Simm, Ralf Drautz, Christoph Ortner, Boris Kozinsky, Gábor Csányi
2021	J	`jnl`	SE(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials. CoRR Simon L. Batzner, Tess E. Smidt, Lixin Sun, Jonathan P. Mailoa, Mordechai Kornbluth, Nicola Molinari, Boris Kozinsky
2020	J	`jnl`	Multitask machine learning of collective variables for enhanced sampling of rare events. CoRR Lixin Sun, Jonathan Vandermause, Simon L. Batzner, Yu Xie, David Clark, Wei Chen, Boris Kozinsky
2019	J	`jnl`	A fast neural network approach for direct covariant forces prediction in complex multi-element extended systems. Nat. Mach. Intell. Jonathan P. Mailoa, Mordechai Kornbluth, Simon L. Batzner, Georgy Samsonidze, Stephen T. Lam, Jonathan Vandermause, Chris Ablitt, Nicola Molinari, Boris Kozinsky
2019	J	`jnl`	Fast Neural Network Approach for Direct Covariant Forces Prediction in Complex Multi-Element Extended Systems. CoRR Jonathan P. Mailoa, Mordechai Kornbluth, Simon L. Batzner, Georgy Samsonidze, Stephen T. Lam, Chris Ablitt, Nicola Molinari, Boris Kozinsky