Pre-training of Molecular GNNs via Conditional Boltzmann Generator

Pre-training of Molecular GNNs via Conditional Boltzmann Generator

20 December 2023

Shigehiko Kanaya

Papers citing "Pre-training of Molecular GNNs via Conditional Boltzmann Generator"

8 / 8 papers shown

Title
Molecular Geometry Pretraining with SE(3)-Invariant Denoising Distance Matching Shengchao Liu Hongyu Guo Jian Tang 47 79 0 27 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 85 124 0 31 May 2022
GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation Minkai Xu Lantao Yu Yang Song Chence Shi Stefano Ermon Jian Tang BDL DiffM 120 502 0 06 Mar 2022
Pre-training Molecular Graph Representation with 3D Geometry Shengchao Liu Hanchen Wang Weiyang Liu Joan Lasenby Hongyu Guo Jian Tang 159 312 0 07 Oct 2021
SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks F. Fuchs Daniel E. Worrall Volker Fischer Max Welling 3DPC 119 683 0 18 Jun 2020
How Powerful are Graph Neural Networks? Keyulu Xu Weihua Hu J. Leskovec Stefanie Jegelka GNN 204 7,554 0 01 Oct 2018
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 143 2,911 0 07 Oct 2016
Convolutional Networks on Graphs for Learning Molecular Fingerprints David Duvenaud D. Maclaurin J. Aguilera-Iparraguirre Rafael Gómez-Bombarelli Timothy D. Hirzel Alán Aspuru-Guzik Ryan P. Adams GNN 179 3,337 0 30 Sep 2015