Bayesian Graph Neural Networks with Adaptive Connection Sampling

7 June 2020

Mingyuan Zhou

Papers citing "Bayesian Graph Neural Networks with Adaptive Connection Sampling"

32 / 32 papers shown

Title
Effects of Random Edge-Dropping on Over-Squashing in Graph Neural Networks Jasraj Singh Keyue Jiang Brooks Paige Laura Toni 70 1 0 11 Feb 2025
FedGrAINS: Personalized SubGraph Federated Learning with Adaptive Neighbor Sampling Emir Ceyani Han Xie Baturalp Buyukates Carl Yang Salman Avestimehr FedML 97 0 0 22 Jan 2025
Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations Richard Bergna Sergio Calvo-Ordoñez Felix L. Opolka Pietro Liò Jose Miguel Hernandez-Lobato BDL 39 2 0 28 Aug 2024
Uncertainty in Graph Neural Networks: A Survey Fangxin Wang Yuqing Liu Kay Liu Yibo Wang Sourav Medya Philip S. Yu AI4CE 48 8 0 11 Mar 2024
Adaptive Message Passing: A General Framework to Mitigate Oversmoothing, Oversquashing, and Underreaching Federico Errica Henrik Christiansen Viktor Zaverkin Takashi Maruyama Mathias Niepert Francesco Alesiani 60 7 0 27 Dec 2023
Graph Convolutional Network with Connectivity Uncertainty for EEG-based Emotion Recognition Hongxiang Gao Xiangyao Wang Zhenghua Chen Min-man Wu Zhipeng Cai Lulu Zhao Jianqing Li Chengyu Liu 38 9 0 22 Oct 2023
A Survey on Oversmoothing in Graph Neural Networks T. Konstantin Rusch Michael M. Bronstein Siddhartha Mishra 41 186 0 20 Mar 2023
A Comprehensive Survey on Graph Summarization with Graph Neural Networks Nasrin Shabani Jia Wu Amin Beheshti Quan.Z Sheng Jin Foo Venus Haghighi Ambreen Hanif Maryam Shahabikargar GNN AI4TS 40 12 0 13 Feb 2023
Understanding and Improving Deep Graph Neural Networks: A Probabilistic Graphical Model Perspective Jiayuan Chen Xiang Zhang Yinfei Xu Tianli Zhao Renjie Xie Wei Xu GNN BDL 23 0 0 25 Jan 2023
Distribution Free Prediction Sets for Node Classification J. Clarkson AI4CE 43 24 0 26 Nov 2022
JuryGCN: Quantifying Jackknife Uncertainty on Graph Convolutional Networks Jian Kang Qinghai Zhou Hanghang Tong UQCV 41 21 0 12 Oct 2022
Robust Node Classification on Graphs: Jointly from Bayesian Label Transition and Topology-based Label Propagation Jun Zhuang M. Hasan 36 20 0 21 Aug 2022
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection Bingzhe Wu Jintang Li Junchi Yu Yatao Bian Hengtong Zhang ... Guangyu Sun Peng Cui Zibin Zheng Zhe Liu P. Zhao OOD 45 25 0 20 May 2022
A General Framework for quantifying Aleatoric and Epistemic uncertainty in Graph Neural Networks Sai Munikoti D. Agarwal Laya Das Balasubramaniam Natarajan BDL UD 31 13 0 20 May 2022
MoReL: Multi-omics Relational Learning Arman Hasanzadeh Ehsan Hajiramezanali N. Duffield Xiaoning Qian 24 7 0 15 Mar 2022
Sparsification and Filtering for Spatial-temporal GNN in Multivariate Time-series Yuanrong Wang T. Aste AI4TS 26 10 0 08 Mar 2022
Recent Advances in Reliable Deep Graph Learning: Inherent Noise, Distribution Shift, and Adversarial Attack Jintang Li Bingzhe Wu Chengbin Hou Guoji Fu Yatao Bian Liang Chen Junzhou Huang Zibin Zheng OOD AAML 32 6 0 15 Feb 2022
Over-smoothing Effect of Graph Convolutional Networks Fang Sun 36 1 0 30 Jan 2022
Confidence May Cheat: Self-Training on Graph Neural Networks under Distribution Shift Hongrui Liu Binbin Hu Xiao Wang Chuan Shi Qing Cui Jun Zhou 94 55 0 27 Jan 2022
Decoupling the Depth and Scope of Graph Neural Networks Hanqing Zeng Muhan Zhang Yinglong Xia Ajitesh Srivastava Andrey Malevich Rajgopal Kannan Viktor Prasanna Long Jin Ren Chen GNN 33 144 0 19 Jan 2022
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification Maximilian Stadler Bertrand Charpentier Simon Geisler Daniel Zügner Stephan Günnemann UQCV BDL 41 81 0 26 Oct 2021
TyXe: Pyro-based Bayesian neural nets for Pytorch H. Ritter Theofanis Karaletsos OOD MU BDL 31 6 0 01 Oct 2021
Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study Tianlong Chen Kaixiong Zhou Keyu Duan Wenqing Zheng Peihao Wang Xia Hu Zhangyang Wang AAML GNN 27 61 0 24 Aug 2021
Dirichlet Energy Constrained Learning for Deep Graph Neural Networks Kaixiong Zhou Xiao Shi Huang Daochen Zha Rui Chen Li Li Soo-Hyun Choi Xia Hu GNN AI4CE 33 113 0 06 Jul 2021
Training Graph Neural Networks with 1000 Layers Guohao Li Matthias Muller Guohao Li V. Koltun GNN AI4CE 51 235 0 14 Jun 2021
Graph Classification by Mixture of Diverse Experts Fenyu Hu Liping Wang Shu Wu Liang Wang Tieniu Tan 42 10 0 29 Mar 2021
Sampling methods for efficient training of graph convolutional networks: A survey Xin Liu Yurui Lai Lei Deng Guoqi Li Xiaochun Ye Xiaochun Ye GNN 29 100 0 10 Mar 2021
NCGNN: Node-Level Capsule Graph Neural Network for Semisupervised Classification Rui Yang Wenrui Dai Chenglin Li Junni Zou H. Xiong 28 20 0 07 Dec 2020
Uncertainty-aware Attention Graph Neural Network for Defending Adversarial Attacks Boyuan Feng Yuke Wang Zhigang Wang Yufei Ding AAML 13 34 0 22 Sep 2020
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference Y. Gal Zoubin Ghahramani UQCV BDL 202 745 0 06 Jun 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,145 0 06 Jun 2015
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,638 0 03 Jul 2012