Cartesian atomic cluster expansion for machine learning interatomic potentials

12 February 2024

Papers citing "Cartesian atomic cluster expansion for machine learning interatomic potentials"

15 / 15 papers shown

Title
Cross-functional transferability in universal machine learning interatomic potentials Xu Huang B. Deng Peichen Zhong Aaron D. Kaplan Kristin A. Persson Gerbrand Ceder 24 0 0 07 Apr 2025
Machine learning interatomic potential can infer electrical response Peichen Zhong Dongjin Kim Daniel S. King Bingqing Cheng 18 1 0 07 Apr 2025
Quantifying Robustness: A Benchmarking Framework for Deep Learning Forecasting in Cyber-Physical Systems Alexander Windmann Henrik S. Steude Daniel Boschmann Oliver Niggemann OOD AI4TS 31 0 0 04 Apr 2025
Optimal Invariant Bases for Atomistic Machine Learning Alice Allen Emily Shinkle Roxana Bujack Nicholas Lubbers 32 0 0 30 Mar 2025
Learning charges and long-range interactions from energies and forces Dongjin Kim Daniel S. King Peichen Zhong Bingqing Cheng 79 4 0 19 Dec 2024
The Importance of Being Scalable: Improving the Speed and Accuracy of Neural Network Interatomic Potentials Across Chemical Domains Eric Qu Aditi S. Krishnapriyan LRM 18 10 0 31 Oct 2024
On the design space between molecular mechanics and machine learning force fields Yuanqing Wang Kenichiro Takaba Michael S. Chen Marcus Wieder Yuzhi Xu ... Kyunghyun Cho Joe G. Greener Peter K. Eastman Stefano Martiniani M. Tuckerman AI4CE 32 4 0 03 Sep 2024
Latent Ewald summation for machine learning of long-range interactions Bingqing Cheng 16 7 0 27 Aug 2024
Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing Viktor Zaverkin Francesco Alesiani Takashi Maruyama Federico Errica Henrik Christiansen Makoto Takamoto Nicolas Weber Mathias Niepert 36 5 0 23 May 2024
Response Matching for generating materials and molecules Bingqing Cheng DiffM 14 1 0 15 May 2024
Overcoming systematic softening in universal machine learning interatomic potentials by fine-tuning Bowen Deng Yunyeong Choi Peichen Zhong Janosh Riebesell Shashwat Anand Zhuohan Li KyuJung Jun Kristin A. Persson Gerbrand Ceder AI4CE 24 16 0 11 May 2024
Interpolation and differentiation of alchemical degrees of freedom in machine learning interatomic potentials Juno Nam Rafael Gómez-Bombarelli AI4CE 27 4 0 16 Apr 2024
Pretraining Strategy for Neural Potentials Zehua Zhang Zijie Li A. Farimani AI4CE 34 0 0 24 Feb 2024
Tensor-reduced atomic density representations James P. Darby D. P. Kovács Ilyes Batatia M. A. Caro G. Hart Christoph Ortner Gábor Csányi 26 32 0 02 Oct 2022
E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials Simon L. Batzner Albert Musaelian Lixin Sun Mario Geiger J. Mailoa M. Kornbluth N. Molinari Tess E. Smidt Boris Kozinsky 188 1,218 0 08 Jan 2021