Learning from Protein Structure with Geometric Vector Perceptrons

3 September 2020

Papers citing "Learning from Protein Structure with Geometric Vector Perceptrons"

7 / 57 papers shown

Title
3DLinker: An E(3) Equivariant Variational Autoencoder for Molecular Linker Design Yinan Huang Xing Peng Jianzhu Ma Muhan Zhang BDL 28 47 0 15 May 2022
Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets Xingang Peng Shitong Luo Jiaqi Guan Qi Xie Jian-wei Peng Jianzhu Ma 17 176 0 15 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 14 494 0 06 Mar 2022
Equivariant Graph Attention Networks for Molecular Property Prediction Tuan Le Frank Noé Djork-Arné Clevert 11 21 0 20 Feb 2022
Improving Molecular Contrastive Learning via Faulty Negative Mitigation and Decomposed Fragment Contrast Yuyang Wang Rishikesh Magar Chen Liang A. Farimani 38 78 0 18 Feb 2022
Geometric and Physical Quantities Improve E(3) Equivariant Message Passing Johannes Brandstetter Rob D. Hesselink Elise van der Pol Erik J. Bekkers Max Welling 17 228 0 06 Oct 2021
Protein sequence-to-structure learning: Is this the end(-to-end revolution)? É. Laine Stephan Eismann A. Elofsson Sergei Grudinin OOD 3DV 15 34 0 16 May 2021