Learning Invariant Molecular Representation in Latent Discrete Space

Learning Invariant Molecular Representation in Latent Discrete Space

22 October 2023

Huajun Chen

Papers citing "Learning Invariant Molecular Representation in Latent Discrete Space"

9 / 9 papers shown

Title
Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization Wenyu Mao Jiancan Wu Haoyang Liu Yongduo Sui Xiang Wang OOD 27 3 0 03 Aug 2024
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook Wenzhao Jiang Hao Liu Hui Xiong CML AI4CE 19 2 0 19 Dec 2023
Discovering Invariant Rationales for Graph Neural Networks Yingmin Wu Xiang Wang An Zhang Xiangnan He Tat-Seng Chua OOD AI4CE 87 170 0 30 Jan 2022
DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery -- A Focus on Affinity Prediction Problems with Noise Annotations Yuanfeng Ji Lu Zhang Jiaxiang Wu Bing Wu Long-Kai Huang ... Ping Luo Shuigeng Zhou Junzhou Huang Peilin Zhao Yatao Bian OOD 49 73 0 24 Jan 2022
Explainability in Graph Neural Networks: A Taxonomic Survey Hao Yuan Haiyang Yu Shurui Gui Shuiwang Ji 156 463 0 31 Dec 2020
Out-of-Distribution Generalization via Risk Extrapolation (REx) David M. Krueger Ethan Caballero J. Jacobsen Amy Zhang Jonathan Binas Dinghuai Zhang Rémi Le Priol Aaron Courville OOD 212 888 0 02 Mar 2020
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
Domain-Adversarial Training of Neural Networks Yaroslav Ganin E. Ustinova Hana Ajakan Pascal Germain Hugo Larochelle François Laviolette M. Marchand Victor Lempitsky GAN OOD 149 9,300 0 28 May 2015
Domain Adaptation: Learning Bounds and Algorithms Yishay Mansour M. Mohri Afshin Rostamizadeh 174 786 0 19 Feb 2009