Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization

Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization

3 August 2024

Papers citing "Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization"

9 / 9 papers shown

Title
Apollo-MILP: An Alternating Prediction-Correction Neural Solving Framework for Mixed-Integer Linear Programming Haoyang Liu Jie Wang Zijie Geng Xijun Li Yuxuan Zong Fangzhou Zhu Jianye Hao Feng Wu 47 1 0 03 Mar 2025
Vague Preference Policy Learning for Conversational Recommendation Gangyi Zhang Chongming Gao Wenqiang Lei Xiaojie Guo Shijun Li Hongshen Chen Zhuozhi Ding Sulong Xu Lingfei Wu 63 1 0 24 Feb 2025
Learning Invariant Molecular Representation in Latent Discrete Space Zhuang Xiang Qiang Zhang Keyan Ding Yatao Bian Xiao Wang Jingsong Lv Hongyang Chen Huajun Chen OOD 20 8 0 22 Oct 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
Robust Optimization as Data Augmentation for Large-scale Graphs Kezhi Kong G. Li Mucong Ding Zuxuan Wu Chen Zhu Bernard Ghanem Gavin Taylor Tom Goldstein 87 63 0 19 Oct 2020
Improved Baselines with Momentum Contrastive Learning Xinlei Chen Haoqi Fan Ross B. Girshick Kaiming He SSL 229 3,029 0 09 Mar 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
Multi-scale Attributed Node Embedding Benedek Rozemberczki Carl Allen Rik Sarkar GNN 139 828 0 28 Sep 2019
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