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"

14 / 14 papers shown

Title
DIVE: Subgraph Disagreement for Graph Out-of-Distribution Generalization Xin Sun Liang Wang Qiang Liu Shu Wu Zilei Wang Liang Wang OOD CML 23 5 0 08 Aug 2024
Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization Wenyu Mao Jiancan Wu Haoyang Liu Yongduo Sui Xiang Wang OOD 30 3 0 03 Aug 2024
UniMoT: Unified Molecule-Text Language Model with Discrete Token Representation Jiayuan Zhu Yunli Qi Yongqiang Chen Quanming Yao 16 1 0 01 Aug 2024
Improving Graph Out-of-distribution Generalization on Real-world Data Can Xu Yao Cheng Jianxiang Yu Haosen Wang Jingsong Lv Xiang Li OOD 16 0 0 14 Jul 2024
Teleporter Theory: A General and Simple Approach for Modeling Cross-World Counterfactual Causality Jiangmeng Li Bin Qin Qirui Ji Yi Li Wenwen Qiang Jianwen Cao Fanjiang Xu 31 0 0 17 Jun 2024
Discrete Dictionary-based Decomposition Layer for Structured Representation Learning Taewon Park Hyun-Chul Kim Minho Lee 23 0 0 11 Jun 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 52 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