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"

31 / 81 papers shown

Title
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 27 105 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 39 370 0 05 Aug 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 24 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 35 173 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 16 1 0 26 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 36 441 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 13 0 0 01 Jun 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 25 176 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 31 65 0 06 Apr 2022
MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design Yuanqi Du Tianfan Fu Jimeng Sun Shengchao Liu AI4CE 25 86 0 28 Mar 2022
Equivariant Graph Attention Networks for Molecular Property Prediction Tuan Le Frank Noé Djork-Arné Clevert 13 21 0 20 Feb 2022
TorchMD-NET: Equivariant Transformers for Neural Network based Molecular Potentials Philipp Thölke Gianni de Fabritiis AI4CE 27 184 0 05 Feb 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
Surrogate- and invariance-boosted contrastive learning for data-scarce applications in science Charlotte Loh T. Christensen Rumen Dangovski Samuel Kim Marin Soljacic 24 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 14 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 13 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 11 25 0 02 Sep 2021
Geometric Deep Learning on Molecular Representations Kenneth Atz F. Grisoni G. Schneider AI4CE 30 286 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 19 135 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 19 47 0 08 Jun 2021
GemNet: Universal Directional Graph Neural Networks for Molecules Johannes Klicpera Florian Becker Stephan Günnemann AI4CE 19 433 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 158 245 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 200 1,232 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