Graph Neural Networks for Molecules

12 September 2022

Papers citing "Graph Neural Networks for Molecules"

24 / 24 papers shown

Title
GraphXForm: Graph transformer for computer-aided molecular design Jonathan Pirnay Jan G. Rittig Alexander B. Wolf Martin Grohe Jakob Burger Alexander Mitsos D. G. Grimm AI4CE 41 1 0 03 Nov 2024
MAGE: Model-Level Graph Neural Networks Explanations via Motif-based Graph Generation Zhaoning Yu Hongyang Gao 31 3 0 21 May 2024
Protein Structure and Sequence Generation with Equivariant Denoising Diffusion Probabilistic Models N. Anand Tudor Achim DiffM 175 170 0 26 May 2022
A 3D Generative Model for Structure-Based Drug Design Shitong Luo Jiaqi Guan Jianzhu Ma Jian-wei Peng DiffM 60 176 0 20 Mar 2022
Improving Molecular Contrastive Learning via Faulty Negative Mitigation and Decomposed Fragment Contrast Yuyang Wang Rishikesh Magar Chen Liang A. Farimani 30 78 0 18 Feb 2022
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 255 7,337 0 11 Nov 2021
DOCKSTRING: easy molecular docking yields better benchmarks for ligand design Miguel García-Ortegón G. Simm Austin Tripp José Miguel Hernández-Lobato A. Bender S. Bacallado 22 73 0 29 Oct 2021
Pre-training Molecular Graph Representation with 3D Geometry Shengchao Liu Hanchen Wang Weiyang Liu Joan Lasenby Hongyu Guo Jian Tang 106 294 0 07 Oct 2021
Top-N: Equivariant set and graph generation without exchangeability Clément Vignac P. Frossard BDL 50 34 0 05 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 33 39 0 30 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 170 125 0 10 Sep 2021
GraphDF: A Discrete Flow Model for Molecular Graph Generation Youzhi Luo Keqiang Yan Shuiwang Ji DRL 157 185 0 01 Feb 2021
Deep Reinforcement Learning Optimizes Graphene Nanopores for Efficient Desalination Yuyang Wang Zhonglin Cao Amir Barati Farimani AI4CE 20 57 0 19 Jan 2021
PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding Saining Xie Jiatao Gu Demi Guo C. Qi Leonidas J. Guibas Or Litany 3DPC 128 618 0 21 Jul 2020
Benchmarking Graph Neural Networks Vijay Prakash Dwivedi Chaitanya K. Joshi Anh Tuan Luu T. Laurent Yoshua Bengio Xavier Bresson 173 907 0 02 Mar 2020
Deep neural network solution of the electronic Schrödinger equation J. Hermann Zeno Schätzle Frank Noé 133 444 0 16 Sep 2019
A Style-Based Generator Architecture for Generative Adversarial Networks Tero Karras S. Laine Timo Aila 262 10,183 0 12 Dec 2018
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models Daniil Polykovskiy Alexander Zhebrak Benjamín Sánchez-Lengeling Sergey Golovanov Oktai Tatanov ... Simon Johansson Hongming Chen Sergey I. Nikolenko Alán Aspuru-Guzik Alex Zhavoronkov ELM 151 628 0 29 Nov 2018
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation Jiaxuan You Bowen Liu Rex Ying Vijay S. Pande J. Leskovec GNN 181 878 0 07 Jun 2018
Conditional molecular design with deep generative models Seokho Kang Kyunghyun Cho BDL 138 182 0 30 Apr 2018
Junction Tree Variational Autoencoder for Molecular Graph Generation Wengong Jin Regina Barzilay Tommi Jaakkola 208 1,205 0 12 Feb 2018
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 152 1,748 0 02 Mar 2017
Interaction Networks for Learning about Objects, Relations and Physics Peter W. Battaglia Razvan Pascanu Matthew Lai Danilo Jimenez Rezende Koray Kavukcuoglu AI4CE OCL PINN GNN 252 1,394 0 01 Dec 2016
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 228 3,202 0 24 Nov 2016