TorchMD-NET: Equivariant Transformers for Neural Network based Molecular Potentials

5 February 2022

Papers citing "TorchMD-NET: Equivariant Transformers for Neural Network based Molecular Potentials"

50 / 112 papers shown

Title
Optimal Invariant Bases for Atomistic Machine Learning Alice Allen Emily Shinkle Roxana Bujack Nicholas Lubbers 37 0 0 30 Mar 2025
Pre-training Graph Neural Networks with Structural Fingerprints for Materials Discovery Shuyi Jia Shitij Govil Manav Ramprasad Victor Fung AI4CE 64 1 0 03 Mar 2025
A Survey of Graph Transformers: Architectures, Theories and Applications Chaohao Yuan Kangfei Zhao Ercan Engin Kuruoglu Liang Wang Tingyang Xu Wenbing Huang Deli Zhao Hong Cheng Yu Rong 51 4 0 23 Feb 2025
MolSpectra: Pre-training 3D Molecular Representation with Multi-modal Energy Spectra Liang Wang Shaozhen Liu Yu Rong Deli Zhao Qiang Liu Shu Wu Liang Wang MedIm 63 2 0 22 Feb 2025
Equivariant Masked Position Prediction for Efficient Molecular Representation Junyi An C. Qu Yun-Fei Shi XinHao Liu Qianwei Tang Fenglei Cao Yuan Qi 35 0 0 12 Feb 2025
A Periodic Bayesian Flow for Material Generation Hanlin Wu Yuxuan Song Jingjing Gong Ziyao Cao Y. Ouyang Jianbing Zhang Hao Zhou Wei-Ying Ma Jingjing Liu DiffM 64 1 0 04 Feb 2025
OpenQDC: Open Quantum Data Commons Cristian Gabellini Nikhil Shenoy Stephan Thaler Semih Cantürk Daniel McNeela Dominique Beaini Michael Bronstein Prudencio Tossou AI4CE 75 1 0 29 Nov 2024
Equivariant Graph Network Approximations of High-Degree Polynomials for Force Field Prediction Zhao Xu Haiyang Yu Montgomery Bohde Shuiwang Ji 40 0 0 06 Nov 2024
Harmformer: Harmonic Networks Meet Transformers for Continuous Roto-Translation Equivariance Tomáš Karella Adam Harmanec J. Kotera Jan Blažek F. Šroubek 36 1 0 06 Nov 2024
Bridging Geometric States via Geometric Diffusion Bridge Shengjie Luo Yixian Xu Di He Shuxin Zheng Tie-Yan Liu Liwei Wang 32 0 0 31 Oct 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 26 10 0 31 Oct 2024
ET-Flow: Equivariant Flow-Matching for Molecular Conformer Generation Majdi Hassan Nikhil Shenoy Jungyoon Lee Hannes Stärk Stephan Thaler Dominique Beaini 27 6 0 29 Oct 2024
Pushing the Limits of All-Atom Geometric Graph Neural Networks: Pre-Training, Scaling and Zero-Shot Transfer Zihan Pengmei Zhengyuan Shen Zichen Wang Marcus Collins Huzefa Rangwala AI4CE 21 2 0 29 Oct 2024
Relaxed Equivariance via Multitask Learning Ahmed A. A. Elhag T. Konstantin Rusch Francesco Di Giovanni Michael Bronstein 42 2 0 23 Oct 2024
CrystalX: Ultra-Precision Crystal Structure Resolution and Error Correction Using Deep Learning Kaipeng Zheng Weiran Huang Wanli Ouyang Han-Sen Zhong Y. Li 29 0 0 17 Oct 2024
Molecular Dynamics and Machine Learning Unlock Possibilities in Beauty Design -- A Perspective Yuzhi Xu Haowei Ni Qinhui Gao Chia-Hua Chang Yanran Huo ... Yike Zhang Radu Grovu Min He John Z. H. Zhang Yuanqing Wang AI4CE 29 0 0 08 Oct 2024
REBIND: Enhancing ground-state molecular conformation via force-based graph rewiring Taewon Kim Hyunjin Seo Sungsoo Ahn Eunho Yang AI4CE 32 1 0 04 Oct 2024
Geometric Representation Condition Improves Equivariant Molecule Generation Zian Li Cai Zhou Xiyuan Wang Xingang Peng Muhan Zhang 42 1 0 04 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 37 4 0 03 Sep 2024
Force-Guided Bridge Matching for Full-Atom Time-Coarsened Dynamics of Peptides Ziyang Yu Wenbing Huang Yang Liu OOD AI4CE 32 1 0 27 Aug 2024
Geometry Informed Tokenization of Molecules for Language Model Generation Xiner Li Limei Wang Youzhi Luo Carl N. Edwards Shurui Gui Yuchao Lin Heng Ji Shuiwang Ji 29 6 0 19 Aug 2024
PlayMolecule pKAce: Small Molecule Protonation through Equivariant Neural Networks Nikolai Schapin Maciej Majewski Mariona Torrens-Fontanals Gianni de Fabritiis 19 1 0 15 Jul 2024
On Machine Learning Approaches for Protein-Ligand Binding Affinity Prediction Nikolai Schapin Carles Navarro Albert Bou Gianni de Fabritiis AI4CE 20 0 0 15 Jul 2024
Pre-training with Fractional Denoising to Enhance Molecular Property Prediction Yuyan Ni Shikun Feng Xin Hong Yuancheng Sun Wei-Ying Ma Zhiming Ma Qiwei Ye Yanyan Lan AI4CE 36 10 0 14 Jul 2024
FreeCG: Free the Design Space of Clebsch-Gordan Transform for Machine Learning Force Fields Shihao Shao Haoran Geng Zun Wang Qinghua Cui 3DV 35 0 0 02 Jul 2024
GeoMFormer: A General Architecture for Geometric Molecular Representation Learning Tianlang Chen Shengjie Luo Di He Shuxin Zheng Tie-Yan Liu Liwei Wang AI4CE 36 5 0 24 Jun 2024
Molecule Graph Networks with Many-body Equivariant Interactions Zetian Mao Jiawen Li Chen Liang Diptesh Das Masato Sumita Koji Tsuda Kelin Xia Koji Tsuda 35 1 0 19 Jun 2024
LLMatDesign: Autonomous Materials Discovery with Large Language Models Shuyi Jia Chao Zhang Victor Fung 46 9 0 19 Jun 2024
Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency Yuchao Lin Jacob Helwig Shurui Gui Shuiwang Ji 39 7 0 11 Jun 2024
Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models Zun Wang Chang-Shu Liu Nianlong Zou He Zhang Xinran Wei Lin Huang Lijun Wu Bin Shao 36 1 0 06 Jun 2024
Neural Polarization: Toward Electron Density for Molecules by Extending Equivariant Networks Bumju Kwak Jeonghee Jo 42 0 0 01 Jun 2024
SE3Set: Harnessing equivariant hypergraph neural networks for molecular representation learning Hongfei Wu Lijun Wu Guoqing Liu Zhirong Liu Bin Shao Zun Wang 35 1 0 26 May 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 41 5 0 23 May 2024
UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning Shikun Feng Yuyan Ni Minghao Li Yanwen Huang Zhiming Ma Wei-Ying Ma Yanyan Lan SSL 41 7 0 15 May 2024
Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction He Zhang Chang-Shu Liu Zun Wang Xinran Wei Siyuan Liu Nanning Zheng Bin Shao Tie-Yan Liu 43 4 0 14 Mar 2024
Generalizing Denoising to Non-Equilibrium Structures Improves Equivariant Force Fields Yi-Lun Liao Tess E. Smidt Abhishek Das DiffM AI4CE 32 12 0 14 Mar 2024
A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications Jiaqi Han Jiacheng Cen Liming Wu Zongzhao Li Xiangzhe Kong ... Zhewei Wei Deli Zhao Yu Rong Wenbing Huang Wenbing Huang AI4CE 34 20 0 01 Mar 2024
TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations Raúl P. Peláez Guillem Simeon Raimondas Galvelis Antonio Mirarchi Peter K. Eastman Stefan Doerr Philipp Thölke T. Markland Gianni de Fabritiis AI4CE 30 12 0 27 Feb 2024
Clifford Group Equivariant Simplicial Message Passing Networks Cong Liu David Ruhe Floor Eijkelboom Patrick Forré 21 13 0 15 Feb 2024
Triplet Interaction Improves Graph Transformers: Accurate Molecular Graph Learning with Triplet Graph Transformers Md Shamim Hussain Mohammed J. Zaki D. Subramanian ViT 26 5 0 07 Feb 2024
On the Completeness of Invariant Geometric Deep Learning Models Zian Li Xiyuan Wang Shijia Kang Muhan Zhang 31 2 0 07 Feb 2024
A Multi-Grained Symmetric Differential Equation Model for Learning Protein-Ligand Binding Dynamics Shengchao Liu Weitao Du Yanjing Li Zhuoxinran Li Vignesh C. Bhethanabotla ... O. Yaghi C. Borgs A. Anandkumar Hongyu Guo J. Chayes AI4CE 32 4 0 26 Jan 2024
Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products Shengjie Luo Tianlang Chen Aditi S. Krishnapriyan 25 19 0 18 Jan 2024
Predicting and Interpreting Energy Barriers of Metallic Glasses with Graph Neural Networks Haoyu Li Shichang Zhang Longwen Tang Mathieu Bauchy Yizhou Sun AI4CE 40 1 0 08 Dec 2023
Sliced Denoising: A Physics-Informed Molecular Pre-Training Method Yuyan Ni Shikun Feng Wei-Ying Ma Zhiming Ma Yanyan Lan DiffM AI4CE 27 10 0 03 Nov 2023
Investigating the Behavior of Diffusion Models for Accelerating Electronic Structure Calculations D. Rothchild Andrew S. Rosen Eric Taw Connie Robinson Joseph E. Gonzalez Aditi S. Krishnapriyan DiffM 24 2 0 02 Nov 2023
Role of Structural and Conformational Diversity for Machine Learning Potentials Nikhil Shenoy Prudencio Tossou Emmanuel Noutahi Hadrien Mary Dominique Beaini Jiarui Ding AI4CE 17 0 0 30 Oct 2023
Navigating protein landscapes with a machine-learned transferable coarse-grained model N. Charron Felix Musil Andrea Guljas Yaoyi Chen Klara Bonneau ... B. Husic Ankit Patel Gianni de Fabritiis Frank Noé C. Clementi AI4CE 16 13 0 27 Oct 2023
From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property Prediction Nima Shoghi Adeesh Kolluru John R. Kitchin Zachary W. Ulissi C. L. Zitnick Brandon M. Wood AI4CE 22 32 0 25 Oct 2023
Learning Interatomic Potentials at Multiple Scales Xiang Fu Albert Musaelian Anders Johansson Tommi Jaakkola Boris Kozinsky 27 2 0 20 Oct 2023