Learning 3D Representations of Molecular Chirality with Invariance to Bond Rotations

8 October 2021

Papers citing "Learning 3D Representations of Molecular Chirality with Invariance to Bond Rotations"

20 / 20 papers shown

Title
$Diffusion Models in $\textit{De Novo}$ Drug Design$ Diffusion Models in $\textit{De Novo}$ Drug Design Amira Alakhdar Barnabás Póczos Newell Washburn MedIm 26 11 0 07 Jun 2024
Predicting the Temperature Dependence of Surfactant CMCs Using Graph Neural Networks Christoforos Brozos Jan G. Rittig Sandip Bhattacharya Elie Akanny Christina Kohlmann Alexander Mitsos 20 4 0 06 Mar 2024
On the Completeness of Invariant Geometric Deep Learning Models Zian Li Xiyuan Wang Shijia Kang Muhan Zhang 31 2 0 07 Feb 2024
SE(3)-Invariant Multiparameter Persistent Homology for Chiral-Sensitive Molecular Property Prediction Andac Demir Francis Prael B. Kiziltan 16 2 0 12 Dec 2023
Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks Yanqiao Zhu Jeehyun Hwang Keir Adams Zhen Liu B. Nan ... Olaf Wiest Olexandr Isayev Connor W. Coley Yizhou Sun Wei Wang 8 2 0 29 Sep 2023
Graph Positional and Structural Encoder Semih Cantürk Renming Liu Olivier Lapointe-Gagné Vincent Létourneau Guy Wolf Dominique Beaini Ladislav Rampášek 25 13 0 14 Jul 2023
ChiENN: Embracing Molecular Chirality with Graph Neural Networks Piotr Gaiñski Michał Koziarski Jacek Tabor Marek Śmieja GNN 27 3 0 05 Jul 2023
A Systematic Survey in Geometric Deep Learning for Structure-based Drug Design Zaixin Zhang Jiaxian Yan Qi Liu Enhong Chen Marinka Zitnik 19 1 0 20 Jun 2023
FAENet: Frame Averaging Equivariant GNN for Materials Modeling Alexandre Duval Victor Schmidt A. Garcia Santiago Miret Fragkiskos D. Malliaros Yoshua Bengio David Rolnick 20 51 0 28 Apr 2023
Knowledge-augmented Graph Machine Learning for Drug Discovery: A Survey from Precision to Interpretability Zhiqiang Zhong A. Barkova Davide Mottin 14 8 0 16 Feb 2023
PhAST: Physics-Aware, Scalable, and Task-specific GNNs for Accelerated Catalyst Design Alexandre Duval Victor Schmidt Santiago Miret Yoshua Bengio Alex Hernández-García David Rolnick 14 7 0 22 Nov 2022
Geometry-Complete Perceptron Networks for 3D Molecular Graphs Alex Morehead Jianlin Cheng GNN 3DV AI4CE 14 12 0 04 Nov 2022
A 3D-Shape Similarity-based Contrastive Approach to Molecular Representation Learning Austin O. Atsango N. Diamant Ziqing Lu Tommaso Biancalani Gabriele Scalia Kangway V Chuang 19 2 0 03 Nov 2022
Predicting Protein-Ligand Binding Affinity with Equivariant Line Graph Network Yi Yi Xu Wan Kangfei Zhao Ou-Yang Le Pei-Ying Zhao 10 1 0 27 Oct 2022
Structure-based Drug Design with Equivariant Diffusion Models Arne Schneuing Yuanqi Du Charles Harris Arian R. Jamasb Ilia Igashov ... Pietro Lió Carla P. Gomes Max Welling Michael M. Bronstein B. Correia DiffM 24 189 0 24 Oct 2022
Graph Neural Networks for Molecules Yuyang Wang Zijie Li A. Farimani GNN AI4CE 41 20 0 12 Sep 2022
ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs Limei Wang Yi Liu Yu-Ching Lin Hao Liu Shuiwang Ji GNN 29 87 0 17 Jun 2022
3D Graph Contrastive Learning for Molecular Property Prediction Kisung Moon Sunyoung Kwon 11 17 0 31 May 2022
MolNet: A Chemically Intuitive Graph Neural Network for Prediction of Molecular Properties Yeji Kim Yoonho Jeong Jihoo Kim E. Lee W. Kim I. Choi GNN 11 7 0 01 Feb 2022
Auto-Encoding Molecular Conformations R. Winter Frank Noé Djork-Arné Clevert AI4CE 34 12 0 05 Jan 2021