Directional Message Passing for Molecular Graphs

6 March 2020

Stephan Günnemann

Papers citing "Directional Message Passing for Molecular Graphs"

50 / 450 papers shown

Title
Multimodal learning with graphs Yasha Ektefaie George Dasoulas Ayush Noori Maha Farhat Marinka Zitnik 51 82 0 07 Sep 2022
Domain-informed graph neural networks: a quantum chemistry case study Jay Morgan A. Paiement C. Klinke GNN 32 4 0 25 Aug 2022
From Static to Dynamic Structures: Improving Binding Affinity Prediction with a Graph-Based Deep Learning Model Yaosen Min Ye Wei Peizhuo Wang Xiao-tong Wang Han Li ... Yu Shi Yingheng Wang Ji Wu Dan Zhao Jianyang Zeng AI4CE 13 2 0 19 Aug 2022
DPA-1: Pretraining of Attention-based Deep Potential Model for Molecular Simulation Duoduo Zhang Hangrui Bi Fu-Zhi Dai Wanrun Jiang Linfeng Zhang Han Wang AI4CE 32 37 0 17 Aug 2022
Conditional Antibody Design as 3D Equivariant Graph Translation Xiangzhe Kong Wenbing Huang Yang Liu DiffM 21 84 0 12 Aug 2022
GEM-2: Next Generation Molecular Property Prediction Network by Modeling Full-range Many-body Interactions Lihang Liu Donglong He Xiaomin Fang Shanzhuo Zhang Fan Wang Jingzhou He Hua-Hong Wu 19 3 0 11 Aug 2022
Motif-based Graph Representation Learning with Application to Chemical Molecules Yifei Wang Shiyang Chen Guobin Chen Ethan Shurberg Hang Liu Pengyu Hong GNN 25 13 0 09 Aug 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
Curvature-informed multi-task learning for graph networks Alexander New M. Pekala Nam Q. Le Janna Domenico C. Piatko Christopher D. Stiles 25 4 0 02 Aug 2022
Graph Neural Network with Local Frame for Molecular Potential Energy Surface Xiyuan Wang Muhan Zhang 38 9 0 01 Aug 2022
Physical Pooling Functions in Graph Neural Networks for Molecular Property Prediction Artur M. Schweidtmann Jan G. Rittig Jana M. Weber Martin Grohe Manuel Dahmen K. Leonhard Alexander Mitsos 14 24 0 27 Jul 2022
Bessel Equivariant Networks for Inversion of Transmission Effects in Multi-Mode Optical Fibres Joshua Mitton S. Mekhail M. Padgett Daniele Faccio Marco Aversa Roderick Murray-Smith 13 1 0 26 Jul 2022
Learning Hierarchical Protein Representations via Complete 3D Graph Networks Limei Wang Haoran Liu Yi Liu Jerry Kurtin Shuiwang Ji GNN 28 55 0 26 Jul 2022
Graph neural networks for the prediction of molecular structure-property relationships Jan G. Rittig Qing-Bin Gao Manuel Dahmen Alexander Mitsos Artur M. Schweidtmann AI4CE 11 10 0 25 Jul 2022
Operation-Level Performance Benchmarking of Graph Neural Networks for Scientific Applications Ryien Hosseini F. Simini V. Vishwanath GNN 15 2 0 20 Jul 2022
e3nn: Euclidean Neural Networks Mario Geiger Tess E. Smidt 35 173 0 18 Jul 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
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
Boosting Heterogeneous Catalyst Discovery by Structurally Constrained Deep Learning Models A. Korovin Innokentiy S. Humonen A. Samtsevich R. Eremin Artem I. Vasilyev V. Lazarev S. Budennyy GNN 14 5 0 11 Jul 2022
Graph-based Molecular Representation Learning Zhichun Guo Kehan Guo B. Nan Yijun Tian Roshni G. Iyer ... Olaf Wiest Xiangliang Zhang Wei Wang Chuxu Zhang Nitesh V. Chawla AI4CE 20 60 0 08 Jul 2022
Spherical Channels for Modeling Atomic Interactions C. L. Zitnick Abhishek Das Adeesh Kolluru Janice Lan Muhammed Shuaibi Anuroop Sriram Zachary W. Ulissi Brandon M. Wood 79 58 0 29 Jun 2022
Persistent homology-based descriptor for machine-learning potential of amorphous structures E. Minamitani I. Obayashi Koji Shimizu S. Watanabe AI4CE 17 11 0 28 Jun 2022
FlowX: Towards Explainable Graph Neural Networks via Message Flows Shurui Gui Hao Yuan Jie Wang Qicheng Lao Kang Li Shuiwang Ji 32 11 0 26 Jun 2022
Edge Direction-invariant Graph Neural Networks for Molecular Dipole Moments Prediction Yang Jeong Park GNN 16 1 0 26 Jun 2022
Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs Yi-Lun Liao Tess E. Smidt 77 213 0 23 Jun 2022
Graph Neural Networks for Temperature-Dependent Activity Coefficient Prediction of Solutes in Ionic Liquids Jan G. Rittig Karim Ben Hicham Artur M. Schweidtmann Manuel Dahmen Alexander Mitsos 8 42 0 23 Jun 2022
Ordered Subgraph Aggregation Networks Chao Qian Gaurav Rattan Floris Geerts Christopher Morris Mathias Niepert 41 56 0 22 Jun 2022
Cluster Generation via Deep Energy-Based Model A. Y. Artsukevich S. Lepeshkin 21 0 0 17 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 28 170 0 17 Jun 2022
Maximum Class Separation as Inductive Bias in One Matrix Tejaswi Kasarla Gertjan J. Burghouts Max van Spengler Elise van der Pol Rita Cucchiara Pascal Mettes 26 22 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 36 441 0 15 Jun 2022
MetaTPTrans: A Meta Learning Approach for Multilingual Code Representation Learning Weiguo Pian Hanyu Peng Xunzhu Tang Tiezhu Sun Haoye Tian Andrew Habib Jacques Klein Tegawende F. Bissyande 11 10 0 13 Jun 2022
Efficient and Accurate Physics-aware Multiplex Graph Neural Networks for 3D Small Molecules and Macromolecule Complexes Shuo-feng Zhang Yang Liu Lei Xie GNN AI4CE 17 12 0 06 Jun 2022
Graph Machine Learning for Design of High-Octane Fuels Jan G. Rittig Martin Ritzert Artur M. Schweidtmann Stefanie Winkler Jana M. Weber P. Morsch K. Heufer Martin Grohe Alexander Mitsos Manuel Dahmen 15 23 0 01 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
Contrastive Representation Learning for 3D Protein Structures Pedro Hermosilla Timo Ropinski 3DV 46 51 0 31 May 2022
3D Graph Contrastive Learning for Molecular Property Prediction Kisung Moon Sunyoung Kwon 13 17 0 31 May 2022
Sampling-free Inference for Ab-Initio Potential Energy Surface Networks Nicholas Gao Stephan Günnemann DiffM 30 18 0 30 May 2022
Spectral Maps for Learning on Subgraphs Marco Pegoraro R. Marin Arianna Rampini Simone Melzi Luca Cosmo Emanuele Rodolà 12 2 0 30 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
Representing Polymers as Periodic Graphs with Learned Descriptors for Accurate Polymer Property Predictions Evan R. Antoniuk Peggy Li B. Kailkhura A. Hiszpanski 25 31 0 27 May 2022
SS-GNN: A Simple-Structured Graph Neural Network for Affinity Prediction Shuke Zhang Yan Jin Tianmeng Liu Qi Wang Zhaohui Zhang Shuliang Zhao Bo Shan 25 32 0 25 May 2022
Asynchronous Neural Networks for Learning in Graphs Lukas Faber Roger Wattenhofer GNN 14 3 0 24 May 2022
Tyger: Task-Type-Generic Active Learning for Molecular Property Prediction Kuangqi Zhou Kaixin Wang Jiashi Feng Jian Tang Tingyang Xu Xinchao Wang 21 1 0 23 May 2022
A graph representation of molecular ensembles for polymer property prediction Matteo Aldeghi Connor W. Coley AI4CE 19 41 0 17 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
Discovering and Explaining the Representation Bottleneck of Graph Neural Networks from Multi-order Interactions Fang Wu Siyuan Li Lirong Wu Dragomir R. Radev Stan Z. Li 27 2 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
The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials Ilyes Batatia Simon L. Batzner D. P. Kovács Albert Musaelian G. Simm R. Drautz Christoph Ortner Boris Kozinsky Gábor Csányi 21 133 0 13 May 2022