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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 / 115 papers shown

Title
Predicting and Interpreting Energy Barriers of Metallic Glasses with Graph Neural Networks Haoyu Li Shichang Zhang Longwen Tang Mathieu Bauchy Yizhou Sun AI4CE 79 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 82 11 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 58 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 68 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 84 14 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 84 37 0 25 Oct 2023
Learning Interatomic Potentials at Multiple Scales Xiang Fu Albert Musaelian Anders Johansson Tommi Jaakkola Boris Kozinsky 81 2 0 20 Oct 2023
Towards equilibrium molecular conformation generation with GFlowNets Alexandra Volokhova Michal Koziarski Alex Hernández-García Cheng-Hao Liu Santiago Miret Pablo Lemos Luca Thiede Zichao Yan Alán Aspuru-Guzik Yoshua Bengio 73 11 0 20 Oct 2023
Equivariant Transformer is all you need Akio Tomiya Yuki Nagai AI4CE 24 7 0 20 Oct 2023
ETDock: A Novel Equivariant Transformer for Protein-Ligand Docking Yi Yi Xu Wan Yatao Bian Ou-Yang Le Peilin Zhao 44 3 0 12 Oct 2023
OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials Peter K. Eastman Raimondas Galvelis Raúl P. Peláez C. Abreu Stephen E. Farr ... Yuanqing Wang Ivy Zhang J. Chodera Gianni De Fabritiis T. Markland AI4CE VLM 86 53 0 04 Oct 2023
EGraFFBench: Evaluation of Equivariant Graph Neural Network Force Fields for Atomistic Simulations Vaibhav Bihani Utkarsh Pratiush Sajid Mannan Tao Du Zhimin Chen Santiago Miret Matthieu Micoulaut M. Smedskjaer Sayan Ranu N. M. A. Krishnan 59 19 0 03 Oct 2023
Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generation Tuan Le Julian Cremer Frank Noé Djork-Arné Clevert Kristof T. Schütt DiffM 131 31 0 29 Sep 2023
From Peptides to Nanostructures: A Euclidean Transformer for Fast and Stable Machine Learned Force Fields J. Frank Oliver T. Unke Klaus-Robert Muller Stefan Chmiela 60 3 0 21 Sep 2023
Latent Representation and Simulation of Markov Processes via Time-Lagged Information Bottleneck Marco Federici Patrick Forré Ryota Tomioka Bastiaan S. Veeling 51 6 0 13 Sep 2023
3D Denoisers are Good 2D Teachers: Molecular Pretraining via Denoising and Cross-Modal Distillation Sungjun Cho Dae-Woong Jeong Sung Moon Ko Jinwoo Kim Sehui Han Seunghoon Hong Honglak Lee Moontae Lee AI4CE DiffM 61 1 0 08 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 21 1 0 01 Sep 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 66 11 0 24 Aug 2023
Crystal Structure Prediction by Joint Equivariant Diffusion Rui Jiao Wen-bing Huang Peijia Lin Jiaqi Han Pin Chen Yutong Lu Yang Liu DiffM 93 70 0 30 Jul 2023
Fractional Denoising for 3D Molecular Pre-training Shi Feng Yuyan Ni Yanyan Lan Zhiming Ma Wei-Ying Ma DiffM AI4CE 106 29 0 20 Jul 2023
Multimodal Molecular Pretraining via Modality Blending Qiying Yu Yudi Zhang Yuyan Ni Shi Feng Yanyan Lan Hao Zhou Jingjing Liu 70 13 0 12 Jul 2023
EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations Yidong Liao Brandon M. Wood Abhishek Das Tess E. Smidt 124 159 0 21 Jun 2023
Top-down machine learning of coarse-grained protein force-fields Carles Navarro Maciej Majewski Gianni De Fabritiis AI4CE 83 12 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 81 24 0 15 Jun 2023
MUBen: Benchmarking the Uncertainty of Molecular Representation Models Yinghao Li Lingkai Kong Yuanqi Du Yue Yu Yuchen Zhuang Wenhao Mu Chao Zhang 84 11 0 14 Jun 2023
TensorNet: Cartesian Tensor Representations for Efficient Learning of Molecular Potentials Guillem Simeon Gianni De Fabritiis 102 49 0 10 Jun 2023
Scaling Spherical CNNs Carlos Esteves Jean-Jacques E. Slotine A. Makadia GNN LRM 70 14 0 08 Jun 2023
Generalist Equivariant Transformer Towards 3D Molecular Interaction Learning Xiangzhe Kong Wen-bing Huang Yang Liu 151 15 0 02 Jun 2023
Smooth, exact rotational symmetrization for deep learning on point clouds Sergey Pozdnyakov Michele Ceriotti 3DPC 97 30 0 30 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 90 92 0 23 May 2023
Clifford Group Equivariant Neural Networks David Ruhe Johannes Brandstetter Patrick Forré 83 42 0 18 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 112 63 0 28 Apr 2023
MUDiff: Unified Diffusion for Complete Molecule Generation Chenqing Hua Sitao Luan Minkai Xu Rex Ying Jie Fu Stefano Ermon Doina Precup DiffM 121 37 0 28 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 87 57 0 20 Apr 2023
Dynamic Graph Representation Learning with Neural Networks: A Survey Leshanshui Yang Sébastien Adam Clément Chatelain AI4TS AI4CE 78 17 0 12 Apr 2023
Highly Accurate Quantum Chemical Property Prediction with Uni-Mol+ Shuqi Lu Zhifeng Gao Di He Linfeng Zhang Guolin Ke 72 28 0 16 Mar 2023
Wigner kernels: body-ordered equivariant machine learning without a basis Filippo Bigi Sergey Pozdnyakov Michele Ceriotti 54 16 0 07 Mar 2023
Denoise Pretraining on Nonequilibrium Molecules for Accurate and Transferable Neural Potentials Yuyang Wang Chang Xu Zijie Li A. Farimani AAML AI4CE 82 22 0 03 Mar 2023
Statistically Optimal Force Aggregation for Coarse-Graining Molecular Dynamics Andreas Krämer Aleksander E. P. Durumeric N. Charron Yaoyi Chen C. Clementi Frank Noé AI4CE 70 22 0 14 Feb 2023
Is Distance Matrix Enough for Geometric Deep Learning? Zian Li Xiyuan Wang Yinan Huang Muhan Zhang 73 19 0 11 Feb 2023
Attending to Graph Transformers Luis Muller Mikhail Galkin Christopher Morris Ladislav Rampášek 97 93 0 08 Feb 2023
GPS++: Reviving the Art of Message Passing for Molecular Property Prediction Dominic Masters Josef Dean Kerstin Klaser Zhiyi Li Sam Maddrell-Mander ... D. Beker Andrew Fitzgibbon Shenyang Huang Ladislav Rampášek Dominique Beaini 110 8 0 06 Feb 2023
Molecular Geometry-aware Transformer for accurate 3D Atomic System modeling Zheng Yuan Yaoyun Zhang Chuanqi Tan Wei Wang Feiran Huang Songfang Huang AI4CE ViT 56 6 0 02 Feb 2023
Spatial Attention Kinetic Networks with E(n)-Equivariance Yuanqing Wang J. Chodera 79 17 0 21 Jan 2023
Machine Learning Coarse-Grained Potentials of Protein Thermodynamics Maciej Majewski Adriana Pérez Philipp Thölke Stefan Doerr N. Charron T. Giorgino B. Husic C. Clementi Frank Noé Gianni De Fabritiis AI4CE 68 76 0 14 Dec 2022
PhAST: Physics-Aware, Scalable, and Task-specific GNNs for Accelerated Catalyst Design Alexandre Duval Victor Schmidt Santiago Miret Yoshua Bengio Alex Hernández-García David Rolnick 77 7 0 22 Nov 2022
Learning the shape of protein micro-environments with a holographic convolutional neural network Michael N. Pun Andrew Ivanov Quinn Bellamy Zachary Montague Colin H. LaMont P. Bradley J. Otwinowski Armita Nourmohammad 49 12 0 05 Nov 2022
Geometry-Complete Perceptron Networks for 3D Molecular Graphs Alex Morehead Jianlin Cheng GNN 3DV AI4CE 53 12 0 04 Nov 2022
Forces are not Enough: Benchmark and Critical Evaluation for Machine Learning Force Fields with Molecular Simulations Xiang Fu Zhenghao Wu Wujie Wang T. Xie S. Keten Rafael Gómez-Bombarelli Tommi Jaakkola 81 146 0 13 Oct 2022
SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials Peter K. Eastman P. Behara David L. Dotson Raimondas Galvelis John E. Herr ... J. Chodera Benjamin P. Pritchard Yuanqing Wang Gianni De Fabritiis T. Markland 117 112 0 21 Sep 2022