Equivariant message passing for the prediction of tensorial properties and molecular spectra

5 February 2021

Oliver T. Unke

Papers citing "Equivariant message passing for the prediction of tensorial properties and molecular spectra"

45 / 95 papers shown

Title
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 32 8 0 06 Feb 2023
Implicit Convolutional Kernels for Steerable CNNs Maksim Zhdanov Nico Hoffmann Gabriele Cesa 32 5 0 12 Dec 2022
Capturing long-range interaction with reciprocal space neural network Hongyu Yu Liangliang Hong Shiyou Chen X. Gong Hongjun Xiang 29 11 0 30 Nov 2022
AdsorbML: A Leap in Efficiency for Adsorption Energy Calculations using Generalizable Machine Learning Potentials Janice Lan Aini Palizhati Muhammed Shuaibi Brandon M. Wood Brook Wander Abhishek Das M. Uyttendaele C. L. Zitnick Zachary W. Ulissi 32 44 0 29 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 13 12 0 05 Nov 2022
PEMP: Leveraging Physics Properties to Enhance Molecular Property Prediction Yuancheng Sun Yimeng Chen Weizhi Ma Wenhao Huang Kang Liu Zhiming Ma Wei-Ying Ma Yanyan Lan 20 7 0 18 Oct 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 32 136 0 13 Oct 2022
Hyperactive Learning (HAL) for Data-Driven Interatomic Potentials Cas van der Oord Matthias Sachs D. P. Kovács Christoph Ortner Gábor Csányi 41 64 0 09 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 32 105 0 21 Sep 2022
Graph neural networks for materials science and chemistry Patrick Reiser Marlen Neubert André Eberhard Luca Torresi Chen Zhou ... Houssam Metni Clint van Hoesel Henrik Schopmans T. Sommer Pascal Friederich GNN AI4CE 50 373 0 05 Aug 2022
Transition1x -- a Dataset for Building Generalizable Reactive Machine Learning Potentials M. Schreiner Arghya Bhowmik T. Vegge Jonas Busk Ole Winther 21 62 0 25 Jul 2022
Thermal half-lives of azobenzene derivatives: virtual screening based on intersystem crossing using a machine learning potential Simon Axelrod E. Shakhnovich Rafael Gómez-Bombarelli 26 20 0 23 Jul 2022
NeuralNEB -- Neural Networks can find Reaction Paths Fast M. Schreiner Arghya Bhowmik T. Vegge Peter Bjørn Jørgensen Ole Winther 41 23 0 20 Jul 2022
e3nn: Euclidean Neural Networks Mario Geiger Tess E. Smidt 40 173 0 18 Jul 2022
Unified 2D and 3D Pre-Training of Molecular Representations Jinhua Zhu Yingce Xia Lijun Wu Shufang Xie Tao Qin Wen-gang Zhou Houqiang Li Tie-Yan Liu AI4CE 54 67 0 14 Jul 2022
Edge Direction-invariant Graph Neural Networks for Molecular Dipole Moments Prediction Yang Jeong Park GNN 23 1 0 26 Jun 2022
The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysts Richard Tran Janice Lan Muhammed Shuaibi Brandon M. Wood Siddharth Goyal ... Jehad Abed Oleksandr Voznyy Edward H. Sargent Zachary W. Ulissi C. L. Zitnick 28 173 0 17 Jun 2022
ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs Limei Wang Yi Liu Yu-Ching Lin Hao Liu Shuiwang Ji GNN 38 89 0 17 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 41 441 0 15 Jun 2022
An Empirical Study of Retrieval-enhanced Graph Neural Networks Dingmin Wang Shengchao Liu Hanchen Wang Bernardo Cuenca Grau Linfeng Song Jian Tang Song Le Qi Liu 15 0 0 01 Jun 2022
Molecular Dipole Moment Learning via Rotationally Equivariant Gaussian Process Regression with Derivatives in Molecular-orbital-based Machine Learning Jiace Sun Lixue Cheng Thomas F. Miller 22 2 0 31 May 2022
3DLinker: An E(3) Equivariant Variational Autoencoder for Molecular Linker Design Yinan Huang Xing Peng Jianzhu Ma Muhan Zhang BDL 30 47 0 15 May 2022
Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets Xingang Peng Shitong Luo Jiaqi Guan Qi Xie Jian-wei Peng Jianzhu Ma 27 176 0 15 May 2022
GemNet-OC: Developing Graph Neural Networks for Large and Diverse Molecular Simulation Datasets Johannes Gasteiger Muhammed Shuaibi Anuroop Sriram Stephan Günnemann Zachary W. Ulissi C. L. Zitnick Abhishek Das AI4TS MLAU 33 66 0 06 Apr 2022
MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design Yuanqi Du Tianfan Fu Jimeng Sun Shengchao Liu AI4CE 31 86 0 28 Mar 2022
Equivariant Graph Attention Networks for Molecular Property Prediction Tuan Le Frank Noé Djork-Arné Clevert 16 21 0 20 Feb 2022
Unsupervised Learning of Group Invariant and Equivariant Representations R. Winter Marco Bertolini Tuan Le Frank Noé Djork-Arné Clevert 25 40 0 15 Feb 2022
TorchMD-NET: Equivariant Transformers for Neural Network based Molecular Potentials Philipp Thölke Gianni De Fabritiis AI4CE 34 186 0 05 Feb 2022
Edge-based Tensor prediction via graph neural networks Yang Zhong Hongyu Yu X. Gong H. Xiang 13 2 0 15 Jan 2022
Equivariant graph neural networks for fast electron density estimation of molecules, liquids, and solids Peter Bjørn Jørgensen Arghya Bhowmik 16 36 0 01 Dec 2021
Directional Message Passing on Molecular Graphs via Synthetic Coordinates Johannes Klicpera Chandan Yeshwanth Stephan Günnemann 42 35 0 08 Nov 2021
Surrogate- and invariance-boosted contrastive learning for data-scarce applications in science Charlotte Loh T. Christensen Rumen Dangovski Samuel Kim Marin Soljacic 29 16 0 15 Oct 2021
Geometric and Physical Quantities Improve E(3) Equivariant Message Passing Johannes Brandstetter Rob D. Hesselink Elise van der Pol Erik J. Bekkers Max Welling 17 229 0 06 Oct 2021
Molformer: Motif-based Transformer on 3D Heterogeneous Molecular Graphs Fang Wu Dragomir R. Radev Huabin Xing ViT 36 54 0 04 Oct 2021
Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments Viktor Zaverkin David Holzmüller Ingo Steinwart Johannes Kastner 21 19 0 20 Sep 2021
Heterogeneous relational message passing networks for molecular dynamics simulations Zun Wang Chong Wang Sibo Zhao Yong Xu Shaogang Hao Chang-Yu Hsieh B. Gu W. Duan 19 25 0 02 Sep 2021
Excited state, non-adiabatic dynamics of large photoswitchable molecules using a chemically transferable machine learning potential Simon Axelrod E. Shakhnovich Rafael Gómez-Bombarelli 29 49 0 10 Aug 2021
Geometric Deep Learning on Molecular Representations Kenneth Atz F. Grisoni G. Schneider AI4CE 34 287 0 26 Jul 2021
Scalars are universal: Equivariant machine learning, structured like classical physics Soledad Villar D. Hogg Kate Storey-Fisher Weichi Yao Ben Blum-Smith PINN AI4CE 24 130 0 11 Jun 2021
GeoMol: Torsional Geometric Generation of Molecular 3D Conformer Ensembles O. Ganea L. Pattanaik Connor W. Coley Regina Barzilay K. Jensen W. Green Tommi Jaakkola AI4CE 27 135 0 08 Jun 2021
BIGDML: Towards Exact Machine Learning Force Fields for Materials H. E. Sauceda Luis E Gálvez-González Stefan Chmiela L. O. Paz-Borbón K. Müller A. Tkatchenko AI4CE 26 47 0 08 Jun 2021
GemNet: Universal Directional Graph Neural Networks for Molecules Johannes Klicpera Florian Becker Stephan Günnemann AI4CE 30 434 0 02 Jun 2021
SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects Oliver T. Unke Stefan Chmiela M. Gastegger Kristof T. Schütt H. E. Sauceda K. Müller 174 246 0 01 May 2021
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 206 1,240 0 08 Jan 2021
Deep neural network solution of the electronic Schrödinger equation J. Hermann Zeno Schätzle Frank Noé 149 446 0 16 Sep 2019