Improving Subgraph Recognition with Variational Graph Information Bottleneck

18 December 2021

Papers citing "Improving Subgraph Recognition with Variational Graph Information Bottleneck"

39 / 39 papers shown

Title
Interpretable High-order Knowledge Graph Neural Network for Predicting Synthetic Lethality in Human Cancers Xuexin Chen Ruichu Cai Zhengting Huang Zijian Li Jie Zheng Min Wu 77 0 0 08 Mar 2025
Drop-Bottleneck: Learning Discrete Compressed Representation for Noise-Robust Exploration Jaekyeom Kim Minjung Kim Dongyeon Woo Gunhee Kim 53 17 0 23 Mar 2021
Recognizing Predictive Substructures with Subgraph Information Bottleneck Junchi Yu Tingyang Xu Yu Rong Yatao Bian Junzhou Huang Ran He 38 44 0 20 Mar 2021
On Explainability of Graph Neural Networks via Subgraph Explorations Hao Yuan Haiyang Yu Jie Wang Kang Li Shuiwang Ji FAtt 62 383 0 09 Feb 2021
Parameterized Explainer for Graph Neural Network Dongsheng Luo Wei Cheng Dongkuan Xu Wenchao Yu Bo Zong Haifeng Chen Xiang Zhang 120 546 0 09 Nov 2020
Graph Information Bottleneck Tailin Wu Hongyu Ren Pan Li J. Leskovec AAML 130 231 0 24 Oct 2020
Graph Information Bottleneck for Subgraph Recognition Junchi Yu Tingyang Xu Yu Rong Yatao Bian Junzhou Huang Ran He 38 155 0 12 Oct 2020
Graph Cross Networks with Vertex Infomax Pooling Maosen Li Siheng Chen Ya Zhang Ivor W. Tsang 85 59 0 05 Oct 2020
Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking Michael Schlichtkrull Nicola De Cao Ivan Titov AI4CE 55 217 0 01 Oct 2020
Subgraph Neural Networks Emily Alsentzer S. G. Finlayson Michelle M. Li Marinka Zitnik GNN 105 135 0 18 Jun 2020
What Makes for Good Views for Contrastive Learning? Yonglong Tian Chen Sun Ben Poole Dilip Krishnan Cordelia Schmid Phillip Isola SSL 75 1,313 0 20 May 2020
Unsupervised Speech Decomposition via Triple Information Bottleneck Kaizhi Qian Yang Zhang Shiyu Chang David D. Cox M. Hasegawa-Johnson 53 178 0 23 Apr 2020
Restricting the Flow: Information Bottlenecks for Attribution Karl Schulz Leon Sixt Federico Tombari Tim Landgraf FAtt 26 183 0 02 Jan 2020
ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations Ekagra Ranjan Soumya Sanyal Partha P. Talukdar GNN 108 330 0 18 Nov 2019
Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck Maximilian Igl K. Ciosek Yingzhen Li Sebastian Tschiatschek Cheng Zhang Sam Devlin Katja Hofmann OffRL 44 172 0 28 Oct 2019
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization Fan-Yun Sun Jordan Hoffmann Vikas Verma Jian Tang SSL 138 852 0 31 Jul 2019
DropEdge: Towards Deep Graph Convolutional Networks on Node Classification Yu Rong Wenbing Huang Tingyang Xu Junzhou Huang 72 1,323 0 25 Jul 2019
Semi-Supervised Graph Classification: A Hierarchical Graph Perspective Jia Li Yu Rong Hong Cheng Helen Meng Wen-bing Huang Junzhou Huang 32 149 0 10 Apr 2019
DeepGCNs: Can GCNs Go as Deep as CNNs? Ge Li Matthias Muller Ali K. Thabet Guohao Li 3DPC GNN 110 1,333 0 07 Apr 2019
Significance-aware Information Bottleneck for Domain Adaptive Semantic Segmentation Yawei Luo Ping Liu T. Guan Junqing Yu Yi Yang 45 184 0 01 Apr 2019
GNNExplainer: Generating Explanations for Graph Neural Networks Rex Ying Dylan Bourgeois Jiaxuan You Marinka Zitnik J. Leskovec LLMAG 111 1,300 0 10 Mar 2019
InfoBot: Transfer and Exploration via the Information Bottleneck Anirudh Goyal Riashat Islam Daniel Strouse Zafarali Ahmed M. Botvinick Hugo Larochelle Yoshua Bengio Sergey Levine OffRL 43 166 0 30 Jan 2019
How Powerful are Graph Neural Networks? Keyulu Xu Weihua Hu J. Leskovec Stefanie Jegelka GNN 173 7,554 0 01 Oct 2018
Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow Xue Bin Peng Angjoo Kanazawa Sam Toyer Pieter Abbeel Sergey Levine 56 214 0 01 Oct 2018
Adaptive Sampling Towards Fast Graph Representation Learning Wen-bing Huang Tong Zhang Yu Rong Junzhou Huang GNN 66 490 0 14 Sep 2018
Hierarchical Graph Representation Learning with Differentiable Pooling Rex Ying Jiaxuan You Christopher Morris Xiang Ren William L. Hamilton J. Leskovec GNN 223 2,135 0 22 Jun 2018
Junction Tree Variational Autoencoder for Molecular Graph Generation Wengong Jin Regina Barzilay Tommi Jaakkola 291 1,358 0 12 Feb 2018
FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling Jie Chen Tengfei Ma Cao Xiao GNN 120 1,514 0 30 Jan 2018
MINE: Mutual Information Neural Estimation Mohamed Ishmael Belghazi A. Baratin Sai Rajeswar Sherjil Ozair Yoshua Bengio Aaron Courville R. Devon Hjelm DRL 143 1,264 0 12 Jan 2018
Graph Attention Networks Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Lio Yoshua Bengio GNN 319 19,991 0 30 Oct 2017
Inductive Representation Learning on Large Graphs William L. Hamilton Z. Ying J. Leskovec 403 15,066 0 07 Jun 2017
Concrete Dropout Y. Gal Jiri Hron Alex Kendall BDL UQCV 129 587 0 22 May 2017
Neural Message Passing for Quantum Chemistry Justin Gilmer S. Schoenholz Patrick F. Riley Oriol Vinyals George E. Dahl 295 7,388 0 04 Apr 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 120 5,920 0 04 Mar 2017
Deep Variational Information Bottleneck Alexander A. Alemi Ian S. Fischer Joshua V. Dillon Kevin Patrick Murphy 83 1,697 0 01 Dec 2016
Information Dropout: Learning Optimal Representations Through Noisy Computation Alessandro Achille Stefano Soatto OOD DRL SSL 42 397 0 04 Nov 2016
Categorical Reparameterization with Gumbel-Softmax Eric Jang S. Gu Ben Poole BDL 221 5,323 0 03 Nov 2016
Semi-Supervised Classification with Graph Convolutional Networks Thomas Kipf Max Welling GNN SSL 447 28,901 0 09 Sep 2016
Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning M. Rupp A. Tkatchenko K. Müller O. A. von Lilienfeld AI4CE 120 1,581 0 12 Sep 2011