Directional Message Passing for Molecular Graphs

6 March 2020

Stephan Günnemann

Papers citing "Directional Message Passing for Molecular Graphs"

50 / 450 papers shown

Title
Relative Molecule Self-Attention Transformer Lukasz Maziarka Dawid Majchrowski Tomasz Danel Piotr Gaiñski Jacek Tabor Igor T. Podolak Pawel M. Morkisz Stanislaw Jastrzebski MedIm 32 34 0 12 Oct 2021
Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions Nicholas Gao Stephan Günnemann 19 36 0 11 Oct 2021
Learning 3D Representations of Molecular Chirality with Invariance to Bond Rotations Keir Adams L. Pattanaik Connor W. Coley 19 32 0 08 Oct 2021
3D Infomax improves GNNs for Molecular Property Prediction Hannes Stärk Dominique Beaini Gabriele Corso Prudencio Tossou Christian Dallago Stephan Günnemann Pietro Lió AI4CE 25 203 0 08 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
Attentive Walk-Aggregating Graph Neural Networks M. F. Demirel Shengchao Liu Siddhant Garg Zhenmei Shi Yingyu Liang 87 9 0 06 Oct 2021
Geometric Algebra Attention Networks for Small Point Clouds Matthew Spellings 3DPC 45 12 0 05 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
Motif-based Graph Self-Supervised Learning for Molecular Property Prediction Zaixin Zhang Qi Liu Hao Wang Chengqiang Lu Chee-Kong Lee SSL AI4CE 32 248 0 03 Oct 2021
Reconstruction for Powerful Graph Representations Leonardo Cotta Christopher Morris Bruno Ribeiro AI4CE 124 78 0 01 Oct 2021
Molecule3D: A Benchmark for Predicting 3D Geometries from Molecular Graphs Zhao Xu Youzhi Luo Xuan Zhang Xinyi Xu Yaochen Xie Meng Liu Kaleb Dickerson Cheng Deng Maho Nakata Shuiwang Ji 35 39 0 30 Sep 2021
GeomGCL: Geometric Graph Contrastive Learning for Molecular Property Prediction Shuangli Li Jingbo Zhou Tong Bill Xu Dejing Dou Hui Xiong AI4CE 28 118 0 24 Sep 2021
Efficient, Interpretable Graph Neural Network Representation for Angle-dependent Properties and its Application to Optical Spectroscopy Tim Hsu Tuan Anh Pham N. Keilbart Stephen E. Weitzner James Chapman Penghao Xiao Shenghao Qiu Xiao Chen B. Wood 22 3 0 23 Sep 2021
Federated Learning of Molecular Properties with Graph Neural Networks in a Heterogeneous Setting Wei-wei Zhu Jiebo Luo Andrew D. White FedML 20 32 0 15 Sep 2021
Differentiable Physics: A Position Piece Bharath Ramsundar Dilip Krishnamurthy V. Viswanathan PINN AI4CE 32 14 0 14 Sep 2021
Inverse design of 3d molecular structures with conditional generative neural networks Niklas W. A. Gebauer M. Gastegger Stefaan S. P. Hessmann Klaus-Robert Muller Kristof T. Schütt AI4CE 187 166 0 10 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
Whole Brain Vessel Graphs: A Dataset and Benchmark for Graph Learning and Neuroscience (VesselGraph) Johannes C. Paetzold J. McGinnis Suprosanna Shit Ivan Ezhov Paul Büschl ... Anjany Sekuboyina Georgios Kaissis Ali Ertürk Stephan Günnemann Bjoern H. Menze 19 9 0 30 Aug 2021
Excited state, non-adiabatic dynamics of large photoswitchable molecules using a chemically transferable machine learning potential Simon Axelrod E. Shakhnovich Rafael Gómez-Bombarelli 13 49 0 10 Aug 2021
6DCNN with roto-translational convolution filters for volumetric data processing Dmitrii Zhemchuzhnikov Ilia Igashov Sergei Grudinin 3DPC 22 2 0 26 Jul 2021
Geometric Deep Learning on Molecular Representations Kenneth Atz F. Grisoni G. Schneider AI4CE 30 286 0 26 Jul 2021
Structure-aware Interactive Graph Neural Networks for the Prediction of Protein-Ligand Binding Affinity Shuangli Li Jingbo Zhou Tong Bill Xu Liang Huang Fan Wang Haoyi Xiong Weili Huang Dejing Dou Hui Xiong MLAU 14 165 0 21 Jul 2021
Property-Aware Relation Networks for Few-Shot Molecular Property Prediction Yaqing Wang Abulikemu Abuduweili Quanming Yao Dejing Dou 26 67 0 16 Jul 2021
Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and More Johannes Klicpera Marten Lienen Stephan Günnemann OT 17 13 0 14 Jul 2021
GeoT: A Geometry-aware Transformer for Reliable Molecular Property Prediction and Chemically Interpretable Representation Learning Bumju Kwak J. Park Taewon Kang Jeonghee Jo Byunghan Lee Sungroh Yoon AI4CE 21 6 0 29 Jun 2021
Rotation Invariant Graph Neural Networks using Spin Convolutions Muhammed Shuaibi Adeesh Kolluru Abhishek Das Aditya Grover Anuroop Sriram Zachary W. Ulissi C. L. Zitnick AI4CE 8 67 0 17 Jun 2021
Large-Scale Chemical Language Representations Capture Molecular Structure and Properties Jerret Ross Brian M. Belgodere Vijil Chenthamarakshan Inkit Padhi Youssef Mroueh Payel Das AI4CE 19 272 0 17 Jun 2021
Fast Quantum Property Prediction via Deeper 2D and 3D Graph Networks Meng Liu Cong Fu Xuan Zhang Limei Wang Yaochen Xie Hao Yuan Youzhi Luo Zhao Xu Shenglong Xu Shuiwang Ji GNN 11 17 0 16 Jun 2021
Simple GNN Regularisation for 3D Molecular Property Prediction & Beyond Jonathan Godwin Michael Schaarschmidt Alex Gaunt Alvaro Sanchez-Gonzalez Yulia Rubanova Petar Velivcković J. Kirkpatrick Peter W. Battaglia 33 60 0 15 Jun 2021
Flexible dual-branched message passing neural network for quantum mechanical property prediction with molecular conformation Jeonghee Jo Bumju Kwak Byunghan Lee Sungroh Yoon 11 2 0 14 Jun 2021
ChemRL-GEM: Geometry Enhanced Molecular Representation Learning for Property Prediction Xiaomin Fang Lihang Liu Jieqiong Lei Donglong He Shanzhuo Zhang Jingbo Zhou Fan Wang Hua-Hong Wu Haifeng Wang AI4CE 11 430 0 11 Jun 2021
Artificial Intelligence in Drug Discovery: Applications and Techniques Jianyuan Deng Zhibo Yang Iwao Ojima Dimitris Samaras Fusheng Wang AI4TS 21 99 0 09 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
SpreadGNN: Serverless Multi-task Federated Learning for Graph Neural Networks Chaoyang He Emir Ceyani Keshav Balasubramanian M. Annavaram Salman Avestimehr FedML 17 50 0 04 Jun 2021
Detect the Interactions that Matter in Matter: Geometric Attention for Many-Body Systems Thorben Frank Stefan Chmiela 13 3 0 04 Jun 2021
GemNet: Universal Directional Graph Neural Networks for Molecules Johannes Klicpera Florian Becker Stephan Günnemann AI4CE 19 433 0 02 Jun 2021
Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting Stephan Thaler J. Zavadlav 15 66 0 02 Jun 2021
Informing Geometric Deep Learning with Electronic Interactions to Accelerate Quantum Chemistry Zhuoran Qiao Anders S. Christensen Matthew Welborn F. Manby Anima Anandkumar Thomas F. Miller 16 74 0 31 May 2021
Symmetry-driven graph neural networks Francesco Farina E. Slade 32 4 0 28 May 2021
E(n) Equivariant Normalizing Flows Victor Garcia Satorras Emiel Hoogeboom F. Fuchs Ingmar Posner Max Welling BDL 29 168 0 19 May 2021
The Power of the Weisfeiler-Leman Algorithm for Machine Learning with Graphs Christopher Morris Matthias Fey Nils M. Kriege GNN 26 23 0 12 May 2021
Learning Gradient Fields for Molecular Conformation Generation Chence Shi Shitong Luo Minkai Xu Jian Tang DiffM AI4CE 31 210 0 09 May 2021
HamNet: Conformation-Guided Molecular Representation with Hamiltonian Neural Networks Ziyao Li Shuwen Yang Guojie Song Lingsheng Cai 8 21 0 08 May 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
Knowledge-aware Contrastive Molecular Graph Learning Yin Fang Haihong Yang Zhuang Xiang Xin Shao Xiaohui Fan Huajun Chen 24 19 0 24 Mar 2021
DIG: A Turnkey Library for Diving into Graph Deep Learning Research Meng Liu Youzhi Luo Limei Wang Yaochen Xie Haonan Yuan ... Haoran Liu Cong Fu Bora Oztekin Xuan Zhang Shuiwang Ji GNN 16 118 0 23 Mar 2021
Language-Agnostic Representation Learning of Source Code from Structure and Context Daniel Zügner Tobias Kirschstein Michele Catasta J. Leskovec Stephan Günnemann 25 119 0 21 Mar 2021
Size-Invariant Graph Representations for Graph Classification Extrapolations Beatrice Bevilacqua Yangze Zhou Bruno Ribeiro OOD 35 108 0 08 Mar 2021
ForceNet: A Graph Neural Network for Large-Scale Quantum Calculations Weihua Hu Muhammed Shuaibi Abhishek Das Siddharth Goyal Anuroop Sriram J. Leskovec Devi Parikh C. L. Zitnick GNN AI4CE 44 67 0 02 Mar 2021
Persistent Message Passing Heiko Strathmann M. Barekatain Charles Blundell Petar Velickovic 25 15 0 01 Mar 2021