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

8 January 2021

Papers citing "E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials"

50 / 396 papers shown

Title
MatSciML: A Broad, Multi-Task Benchmark for Solid-State Materials Modeling Kin Long Kelvin Lee Carmelo Gonzales Marcel Nassar Matthew Spellings Mikhail Galkin Santiago Miret 35 15 0 12 Sep 2023
Diffusion-EDFs: Bi-equivariant Denoising Generative Modeling on SE(3) for Visual Robotic Manipulation Hyunwoo Ryu Jiwoo Kim Hyun Seok Ahn Junwoo Chang Joohwan Seo Taehan Kim Yubin Kim Chaewon Hwang Jongeun Choi R. Horowitz DiffM 27 33 0 06 Sep 2023
PolyGET: Accelerating Polymer Simulations by Accurate and Generalizable Forcefield with Equivariant Transformer Rui Feng Huan Tran Aubrey Toland Binghong Chen Qi Zhu R. Ramprasad Chao Zhang 11 1 0 01 Sep 2023
Matbench Discovery -- A framework to evaluate machine learning crystal stability predictions Janosh Riebesell Rhys E. A. Goodall Philipp Benner Chiang Yuan Bowen Deng A. Lee Anubhav Jain Kristin A. Persson OOD 36 35 0 28 Aug 2023
SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases Yang Liu Jiashun Cheng Haihong Zhao Tingyang Xu P. Zhao Fugee Tsung Jia Li Yu Rong AI4CE 40 18 0 25 Aug 2023
May the Force be with You: Unified Force-Centric Pre-Training for 3D Molecular Conformations Rui Feng Qi Zhu Huan Tran Binghong Chen Aubrey Toland R. Ramprasad Chao Zhang AI4CE 28 9 0 24 Aug 2023
Beyond MD17: the reactive xxMD dataset Zihan Pengmei Junyu Liu Yinan Shu 23 6 0 22 Aug 2023
SE(3) Equivariant Augmented Coupling Flows Laurence I. Midgley Vincent Stimper Javier Antorán Emile Mathieu Bernhard Schölkopf José Miguel Hernández-Lobato 38 22 0 20 Aug 2023
Accurate machine learning force fields via experimental and simulation data fusion Sebastien Röcken Julija Zavadlav AI4CE 29 12 0 17 Aug 2023
Does AI for science need another ImageNet Or totally different benchmarks? A case study of machine learning force fields Yatao Li Wanling Gao Lei Wang Lixin Sun Zun Wang Jianfeng Zhan 18 1 0 11 Aug 2023
Variational Monte Carlo on a Budget -- Fine-tuning pre-trained Neural Wavefunctions Michael Scherbela Leon Gerard Philipp Grohs 35 5 0 15 Jul 2023
Discovering Symbolic Laws Directly from Trajectories with Hamiltonian Graph Neural Networks S. Bishnoi Ravinder Bhattoo J. Jayadeva Sayan Ranu N. M. A. Krishnan PINN AI4CE 34 1 0 11 Jul 2023
Accelerating Molecular Graph Neural Networks via Knowledge Distillation Filip Ekstrom Kelvinius D. Georgiev Artur P. Toshev Johannes Gasteiger 29 7 0 26 Jun 2023
Accurate melting point prediction through autonomous physics-informed learning O. Klimanova Timofei Miryashkin Alexander Shapeev 4 3 0 23 Jun 2023
EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations Yidong Liao Brandon M. Wood Abhishek Das Tess E. Smidt 26 131 0 21 Jun 2023
Uncertainty Estimation for Molecules: Desiderata and Methods Tom Wollschlager Nicholas Gao Bertrand Charpentier Mohamed Amine Ketata Stephan Günnemann 23 9 0 20 Jun 2023
QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules Haiyang Yu Meng Liu Youzhi Luo A. Strasser X. Qian Xiaoning Qian Shuiwang Ji 18 20 0 15 Jun 2023
On the Interplay of Subset Selection and Informed Graph Neural Networks Niklas Breustedt Paolo Climaco Jochen Garcke J. Hamaekers Gitta Kutyniok D. Lorenz Rick Oerder Chirag Varun Shukla 27 0 0 15 Jun 2023
Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials Shengchao Liu Weitao Du Yanjing Li Zhuoxinran Li Zhiling Zheng ... Anima Anandkumar C. Borgs J. Chayes Hongyu Guo Jian Tang AI4CE 33 20 0 15 Jun 2023
M $^2$ Hub: Unlocking the Potential of Machine Learning for Materials Discovery Yuanqi Du Yingheng Wang Yin-Hua Huang Jianan Canal Li Yanqiao Zhu T. Xie Chenru Duan J. Gregoire Carla P. Gomes 34 6 0 14 Jun 2023
Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction Yu-Ching Lin Keqiang Yan Youzhi Luo Yi Liu Xiaoning Qian Shuiwang Ji 66 33 0 12 Jun 2023
TensorNet: Cartesian Tensor Representations for Efficient Learning of Molecular Potentials Guillem Simeon Gianni De Fabritiis 29 45 0 10 Jun 2023
14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon K. Jablonka Qianxiang Ai Alexander H Al-Feghali S. Badhwar Joshua D. Bocarsly Andres M Bran ... Aristana Scourtas K. J. Schmidt Ian Foster Andrew D. White Ben Blaiszik 40 101 0 09 Jun 2023
Representing and Learning Functions Invariant Under Crystallographic Groups Ryan P. Adams Peter Orbanz 26 4 0 08 Jun 2023
Normalization-Equivariant Neural Networks with Application to Image Denoising Sébastien Herbreteau E. Moebel Charles Kervrann 20 9 0 08 Jun 2023
Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian Haiyang Yu Zhao Xu X. Qian Xiaoning Qian Shuiwang Ji 39 24 0 08 Jun 2023
How does over-squashing affect the power of GNNs? Francesco Di Giovanni T. Konstantin Rusch Michael M. Bronstein Andreea Deac Marc Lackenby Siddhartha Mishra Petar Velivcković 30 34 0 06 Jun 2023
Machine Learning Force Fields with Data Cost Aware Training Alexander Bukharin Tianyi Liu Sheng Wang Simiao Zuo Weihao Gao Wen Yan Tuo Zhao AI4CE 29 0 0 05 Jun 2023
Transfer learning for atomistic simulations using GNNs and kernel mean embeddings Johannes Falk L. Bonati P. Novelli Michele Parinello Massimiliano Pontil 30 4 0 02 Jun 2023
Generalist Equivariant Transformer Towards 3D Molecular Interaction Learning Xiangzhe Kong Wen-bing Huang Yang Liu 22 13 0 02 Jun 2023
Catalysis distillation neural network for the few shot open catalyst challenge B. Deng 11 0 0 31 May 2023
Smooth, exact rotational symmetrization for deep learning on point clouds Sergey Pozdnyakov Michele Ceriotti 3DPC 37 25 0 30 May 2023
SO(2)-Equivariant Downwash Models for Close Proximity Flight Henry Smith Ajay Shankar Jennifer Gielis J. Blumenkamp A. Prorok 29 7 0 30 May 2023
Geometric Algebra Transformer Johann Brehmer P. D. Haan S. Behrends Taco S. Cohen 39 26 0 28 May 2023
Learning Lagrangian Fluid Mechanics with E( $3$ )-Equivariant Graph Neural Networks Artur P. Toshev Gianluca Galletti Johannes Brandstetter Stefan Adami Nikolaus A. Adams AI4CE 27 5 0 24 May 2023
Evaluation of the MACE Force Field Architecture: from Medicinal Chemistry to Materials Science D. P. Kovács Ilyes Batatia E. Arany Gábor Csányi AI4CE 26 82 0 23 May 2023
PANNA 2.0: Efficient neural network interatomic potentials and new architectures Franco Pellegrini Ruggero Lot Yusuf Shaidu E. Küçükbenli 17 9 0 19 May 2023
Clifford Group Equivariant Neural Networks David Ruhe Johannes Brandstetter Patrick Forré 29 35 0 18 May 2023
Policy Gradient Methods in the Presence of Symmetries and State Abstractions Prakash Panangaden S. Rezaei-Shoshtari Rosie Zhao D. Meger Doina Precup 25 2 0 09 May 2023
Equivariant Neural Networks for Spin Dynamics Simulations of Itinerant Magnets Y. Miyazaki 6 4 0 05 May 2023
Importance of equivariant and invariant symmetries for fluid flow modeling Varun Shankar Shivam Barwey Zico Kolter R. Maulik V. Viswanathan AI4CE 24 4 0 03 May 2023
An Exploration of Conditioning Methods in Graph Neural Networks Yeskendir Koishekenov Erik J. Bekkers AI4CE 40 3 0 03 May 2023
Single-model uncertainty quantification in neural network potentials does not consistently outperform model ensembles Aik Rui Tan S. Urata Samuel Goldman Johannes C. B. Dietschreit Rafael Gómez-Bombarelli BDL 38 42 0 02 May 2023
Stress and heat flux via automatic differentiation Marcel F. Langer J. Frank Florian Knoop 30 8 0 02 May 2023
Geometric Latent Diffusion Models for 3D Molecule Generation Minkai Xu Alexander Powers R. Dror Stefano Ermon J. Leskovec DiffM AI4CE 58 135 0 02 May 2023
FAENet: Frame Averaging Equivariant GNN for Materials Modeling Alexandre Duval Victor Schmidt A. Garcia Santiago Miret Fragkiskos D. Malliaros Yoshua Bengio David Rolnick 34 55 0 28 Apr 2023
Accurate Surface and Finite Temperature Bulk Properties of Lithium Metal at Large Scales using Machine Learning Interaction Potentials Mgcini Keith Phuthi A. Yao Simon L. Batzner Albert Musaelian Boris Kozinsky E. D. Cubuk V. Viswanathan 14 11 0 24 Apr 2023
Scaling the leading accuracy of deep equivariant models to biomolecular simulations of realistic size Albert Musaelian A. Johansson Simon L. Batzner Boris Kozinsky 32 48 0 20 Apr 2023
Designing Nonlinear Photonic Crystals for High-Dimensional Quantum State Engineering Eyal Rozenberg Aviv Karnieli O. Yesharim Joshua Foley-Comer Sivan Trajtenberg‐Mills ... Shashi Prabhakar R. Singh Daniel Freedman A. Bronstein A. Arie 18 1 0 13 Apr 2023
Evaluating the Robustness of Interpretability Methods through Explanation Invariance and Equivariance Jonathan Crabbé M. Schaar AAML 24 6 0 13 Apr 2023