A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining

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A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining

28 May 2023

Jian Tang

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Papers citing "A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining"

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Title
Bootstrap your own latent: A new approach to self-supervised Learning Jean-Bastien Grill Florian Strub Florent Altché Corentin Tallec Pierre Harvey Richemond ... M. G. Azar Bilal Piot Koray Kavukcuoglu Rémi Munos Michal Valko SSL 462 6,864 0 13 Jun 2020
GEOM: Energy-annotated molecular conformations for property prediction and molecular generation Simon Axelrod Rafael Gómez-Bombarelli 3DV AI4CE 120 222 0 09 Jun 2020
Open Graph Benchmark: Datasets for Machine Learning on Graphs Weihua Hu Matthias Fey Marinka Zitnik Yuxiao Dong Hongyu Ren Bowen Liu Michele Catasta J. Leskovec 311 2,762 0 02 May 2020
Principal Neighbourhood Aggregation for Graph Nets Gabriele Corso Luca Cavalleri Dominique Beaini Pietro Lio Petar Velickovic GNN 164 678 0 12 Apr 2020
Hierarchical Generation of Molecular Graphs using Structural Motifs Wengong Jin Regina Barzilay Tommi Jaakkola 108 289 0 08 Feb 2020
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization Fan-Yun Sun Jordan Hoffmann Vikas Verma Jian Tang SSL 177 868 0 31 Jul 2019
Generative Modeling by Estimating Gradients of the Data Distribution Yang Song Stefano Ermon SyDa DiffM 268 3,971 0 12 Jul 2019
Strategies for Pre-training Graph Neural Networks Weihua Hu Bowen Liu Joseph Gomes Marinka Zitnik Percy Liang Vijay S. Pande J. Leskovec SSL AI4CE 133 1,419 0 29 May 2019
How Powerful are Graph Neural Networks? Keyulu Xu Weihua Hu J. Leskovec Stefanie Jegelka GNN 289 7,726 0 01 Oct 2018
Deep Graph Infomax Petar Velickovic W. Fedus William L. Hamilton Pietro Lio Yoshua Bengio R. Devon Hjelm GNN 134 2,409 0 27 Sep 2018
Learning deep representations by mutual information estimation and maximization R. Devon Hjelm A. Fedorov Samuel Lavoie-Marchildon Karan Grewal Phil Bachman Adam Trischler Yoshua Bengio SSL DRL 399 2,677 0 20 Aug 2018
Representation Learning with Contrastive Predictive Coding Aaron van den Oord Yazhe Li Oriol Vinyals DRL SSL 360 10,385 0 10 Jul 2018
N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules Shengchao Liu M. F. Demirel Yingyu Liang GNN NAI 67 197 0 24 Jun 2018
Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds Nathaniel Thomas Tess E. Smidt S. Kearnes Lusann Yang Li Li Kai Kohlhoff Patrick F. Riley 3DPC 135 980 0 22 Feb 2018
Neural Message Passing for Quantum Chemistry Justin Gilmer S. Schoenholz Patrick F. Riley Oriol Vinyals George E. Dahl 604 7,512 0 04 Apr 2017
MoleculeNet: A Benchmark for Molecular Machine Learning Zhenqin Wu Bharath Ramsundar Evan N. Feinberg Joseph Gomes C. Geniesse Aneesh S. Pappu K. Leswing Vijay S. Pande OOD 358 1,846 0 02 Mar 2017
Automatic chemical design using a data-driven continuous representation of molecules Rafael Gómez-Bombarelli Jennifer N. Wei David Duvenaud José Miguel Hernández-Lobato Benjamín Sánchez-Lengeling Dennis Sheberla J. Aguilera-Iparraguirre Timothy D. Hirzel Ryan P. Adams Alán Aspuru-Guzik 3DV 222 2,954 0 07 Oct 2016
Deep Unsupervised Learning using Nonequilibrium Thermodynamics Jascha Narain Sohl-Dickstein Eric A. Weiss Niru Maheswaranathan Surya Ganguli SyDa DiffM 347 7,048 0 12 Mar 2015