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
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 24 9 0 20 Oct 2023
Equivariant Transformer is all you need Akio Tomiya Yuki Nagai AI4CE 6 6 0 20 Oct 2023
ETDock: A Novel Equivariant Transformer for Protein-Ligand Docking Yi Yi Xu Wan Yatao Bian Ou-Yang Le Peilin Zhao 13 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 28 36 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 24 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 27 25 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 24 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 16 3 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 30 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 11 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 28 9 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 19 59 0 30 Jul 2023
Fractional Denoising for 3D Molecular Pre-training Shi Feng Yuyan Ni Yanyan Lan Zhiming Ma Wei-Ying Ma DiffM AI4CE 42 25 0 20 Jul 2023
Multimodal Molecular Pretraining via Modality Blending Qiying Yu Yudi Zhang Yuyan Ni Shi Feng Yanyan Lan Hao Zhou Jingjing Liu 21 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 24 131 0 21 Jun 2023
Top-down machine learning of coarse-grained protein force-fields Carles Navarro Maciej Majewski Gianni de Fabritiis AI4CE 13 11 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 13 20 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 22 9 0 14 Jun 2023
TensorNet: Cartesian Tensor Representations for Efficient Learning of Molecular Potentials Guillem Simeon Gianni de Fabritiis 24 45 0 10 Jun 2023
Scaling Spherical CNNs Carlos Esteves Jean-Jacques E. Slotine A. Makadia GNN LRM 19 13 0 08 Jun 2023
Generalist Equivariant Transformer Towards 3D Molecular Interaction Learning Xiangzhe Kong Wen-bing Huang Yang Liu 20 13 0 02 Jun 2023
Smooth, exact rotational symmetrization for deep learning on point clouds Sergey Pozdnyakov Michele Ceriotti 3DPC 35 25 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 24 82 0 23 May 2023
Clifford Group Equivariant Neural Networks David Ruhe Johannes Brandstetter Patrick Forré 24 34 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 20 53 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 45 34 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 27 48 0 20 Apr 2023
Dynamic Graph Representation Learning with Neural Networks: A Survey Leshanshui Yang Sébastien Adam Clément Chatelain AI4TS AI4CE 28 14 0 12 Apr 2023
Highly Accurate Quantum Chemical Property Prediction with Uni-Mol+ Shuqi Lu Zhifeng Gao Di He Linfeng Zhang Guolin Ke 32 24 0 16 Mar 2023
Wigner kernels: body-ordered equivariant machine learning without a basis Filippo Bigi Sergey Pozdnyakov Michele Ceriotti 32 15 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 19 20 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 12 20 0 14 Feb 2023
Is Distance Matrix Enough for Geometric Deep Learning? Zian Li Xiyuan Wang Yinan Huang Muhan Zhang 37 17 0 11 Feb 2023
Attending to Graph Transformers Luis Muller Mikhail Galkin Christopher Morris Ladislav Rampášek 44 85 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 28 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 24 6 0 02 Feb 2023
Spatial Attention Kinetic Networks with E(n)-Equivariance Yuanqing Wang J. Chodera 27 15 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 6 70 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 33 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 11 12 0 05 Nov 2022
Geometry-Complete Perceptron Networks for 3D Molecular Graphs Alex Morehead Jianlin Cheng GNN 3DV AI4CE 24 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 30 136 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 27 105 0 21 Sep 2022
Graph Neural Networks for Molecules Yuyang Wang Zijie Li A. Farimani GNN AI4CE 45 20 0 12 Sep 2022
Graph Neural Network with Local Frame for Molecular Potential Energy Surface Xiyuan Wang Muhan Zhang 30 9 0 01 Aug 2022
Energy-Motivated Equivariant Pretraining for 3D Molecular Graphs Rui Jiao Jiaqi Han Wenbing Huang Yu Rong Yang Liu AI4CE 30 45 0 18 Jul 2022
Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs Yi-Lun Liao Tess E. Smidt 75 213 0 23 Jun 2022
MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields Ilyes Batatia D. P. Kovács G. Simm Christoph Ortner Gábor Csányi 36 441 0 15 Jun 2022
Pre-training via Denoising for Molecular Property Prediction Sheheryar Zaidi Michael Schaarschmidt James Martens Hyunjik Kim Yee Whye Teh Alvaro Sanchez-Gonzalez Peter W. Battaglia Razvan Pascanu Jonathan Godwin DiffM AI4CE 15 121 0 31 May 2022
So3krates: Equivariant attention for interactions on arbitrary length-scales in molecular systems J. Frank Oliver T. Unke Klaus-Robert Muller 11 44 0 28 May 2022