GINTRIP: Interpretable Temporal Graph Regression using Information
bottleneck and Prototype-based method

GINTRIP: Interpretable Temporal Graph Regression using Information bottleneck and Prototype-based method

17 September 2024

Seyed Mohamad Moghadas

Adrian Munteanu

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Papers citing "GINTRIP: Interpretable Temporal Graph Regression using Information bottleneck and Prototype-based method"

10 / 10 papers shown

Title
Interpretable Prototype-based Graph Information Bottleneck Sangwoo Seo Sungwon Kim Chanyoung Park 59 14 0 30 Oct 2023
Rethinking Semantic Segmentation: A Prototype View Tianfei Zhou Wenguan Wang E. Konukoglu Luc Van Gool SSeg 106 273 0 28 Mar 2022
Discovering Invariant Rationales for Graph Neural Networks Yingmin Wu Xiang Wang An Zhang Xiangnan He Tat-Seng Chua OOD AI4CE 153 231 0 30 Jan 2022
Unsupervised Image Segmentation by Mutual Information Maximization and Adversarial Regularization S. E. Mirsadeghi Ali Royat H. Rezatofighi 47 32 0 01 Jul 2021
Spatial-Temporal Graph ODE Networks for Traffic Flow Forecasting Zheng Fang Qingqing Long Guojie Song Kunqing Xie AI4TS 66 476 0 24 Jun 2021
Discrete Graph Structure Learning for Forecasting Multiple Time Series Chao Shang Jie Chen J. Bi CML BDL AI4TS 138 239 0 18 Jan 2021
Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking Michael Schlichtkrull Nicola De Cao Ivan Titov AI4CE 80 218 0 01 Oct 2020
GMAN: A Graph Multi-Attention Network for Traffic Prediction Chuanpan Zheng Xiaoliang Fan Cheng-Yu Wang Jianzhong Qi AI4TS AI4CE 117 1,380 0 11 Nov 2019
XGBoost: A Scalable Tree Boosting System Tianqi Chen Carlos Guestrin 809 38,961 0 09 Mar 2016
Deep Learning and the Information Bottleneck Principle Naftali Tishby Noga Zaslavsky DRL 210 1,591 0 09 Mar 2015