Towards Deeper Graph Neural Networks with Differentiable Group Normalization

12 June 2020

Daochen Zha

Papers citing "Towards Deeper Graph Neural Networks with Differentiable Group Normalization"

50 / 95 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
Resolving Oversmoothing with Opinion Dissensus Keqin Wang Yulong Yang Ishan Saha Christine Allen-Blanchette 60 1 0 31 Jan 2025
Efficient Traffic Prediction Through Spatio-Temporal Distillation Qianru Zhang Xinyi Gao Haixin Wang S. Yiu Hongzhi Yin AI4TS 37 2 0 15 Jan 2025
A Dynamical Systems-Inspired Pruning Strategy for Addressing Oversmoothing in Graph Neural Networks Biswadeep Chakraborty H. Kumar Saibal Mukhopadhyay 82 1 0 10 Dec 2024
COSCO: A Sharpness-Aware Training Framework for Few-shot Multivariate Time Series Classification Jesus Barreda Ashley Gomez Ruben Puga Kaixiong Zhou Li Zhang AI4TS 18 0 0 15 Sep 2024
Detection of False Data Injection Attacks (FDIA) on Power Dynamical Systems With a State Prediction Method Abhijeet Sahu Truc Nguyen Kejun Chen Xiangyu Zhang Malik Hassanaly 29 1 0 06 Sep 2024
Curvy: A Parametric Cross-section based Surface Reconstruction Aradhya Neeraj Mathur Apoorv Khattar Ojaswa Sharma 21 0 0 01 Sep 2024
RW-NSGCN: A Robust Approach to Structural Attacks via Negative Sampling Shuqi He Jun Zhuang Ding Wang Jun Song AAML 35 0 0 13 Aug 2024
Beyond Over-smoothing: Uncovering the Trainability Challenges in Deep Graph Neural Networks Jie Peng Runlin Lei Zhewei Wei 33 5 0 07 Aug 2024
Distribution Learning for Molecular Regression Nima Shoghi Pooya Shoghi Anuroop Sriram Abhishek Das OOD 27 0 0 30 Jul 2024
UniGAP: A Universal and Adaptive Graph Upsampling Approach to Mitigate Over-Smoothing in Node Classification Tasks Xiaotang Wang Yun Zhu Haizhou Shi Yongchao Liu Chuntao Hong 42 2 0 28 Jul 2024
Alleviating Over-Smoothing via Aggregation over Compact Manifolds Dongzhuoran Zhou Hui Yang Bo Xiong Yue Ma Evgeny Kharlamov 41 0 0 27 Jul 2024
Simplifying the Theory on Over-Smoothing Andreas Roth 48 3 0 16 Jul 2024
Foundations and Frontiers of Graph Learning Theory Yu Huang Min Zhou Menglin Yang Zhen Wang Muhan Zhang Jie Wang Hong Xie Hao Wang Defu Lian Enhong Chen AI4CE GNN 55 2 0 03 Jul 2024
SF-GNN: Self Filter for Message Lossless Propagation in Deep Graph Neural Network Yushan Zhu Wen Zhang Yajing Xu Zhen Yao Mingyang Chen Huajun Chen 35 0 0 03 Jul 2024
Bridging Smoothness and Approximation: Theoretical Insights into Over-Smoothing in Graph Neural Networks Guangrui Yang Jianfei Li Ming Li Han Feng Ding-Xuan Zhou 35 1 0 01 Jul 2024
Efficient Sharpness-Aware Minimization for Molecular Graph Transformer Models Yili Wang Kaixiong Zhou Ninghao Liu Ying Wang Xin Wang 40 10 0 19 Jun 2024
GATE: How to Keep Out Intrusive Neighbors Nimrah Mustafa R. Burkholz 47 0 0 01 Jun 2024
Rethinking Independent Cross-Entropy Loss For Graph-Structured Data Rui Miao Kaixiong Zhou Yili Wang Ninghao Liu Ying Wang Xin Wang 42 4 0 24 May 2024
ATNPA: A Unified View of Oversmoothing Alleviation in Graph Neural Networks Yufei Jin Xingquan Zhu 53 2 0 02 May 2024
Optimizing OOD Detection in Molecular Graphs: A Novel Approach with Diffusion Models Xu Shen Yili Wang Kaixiong Zhou Shirui Pan Xin Wang 32 6 0 24 Apr 2024
GRANOLA: Adaptive Normalization for Graph Neural Networks Moshe Eliasof Beatrice Bevilacqua Carola-Bibiane Schönlieb Haggai Maron 33 5 0 20 Apr 2024
Exploring the Efficacy of Group-Normalization in Deep Learning Models for Alzheimer's Disease Classification Gousia Habib Ishfaq Ahmed Malik Jameel Ahmad Imtiaz Ahmed Shaima Qureshi 34 0 0 01 Apr 2024
On the Topology Awareness and Generalization Performance of Graph Neural Networks Junwei Su Chuan Wu AI4CE 32 0 0 07 Mar 2024
Structure-based out-of-distribution (OOD) materials property prediction: a benchmark study Sadman Sadeed Omee Nihang Fu Rongzhi Dong Ming Hu Jianjun Hu OOD 31 17 0 16 Jan 2024
Are GATs Out of Balance? Nimrah Mustafa Aleksandar Bojchevski R. Burkholz 48 4 0 11 Oct 2023
Learning How to Propagate Messages in Graph Neural Networks Teng Xiao Zhengyu Chen Donglin Wang Suhang Wang GNN 28 76 0 01 Oct 2023
Unsupervised Learning via Network-Aware Embeddings Anne Sophie Riis Damstrup Sofie Tosti Madsen Michele Coscia SSL 35 0 0 19 Sep 2023
Reconstructing Groups of People with Hypergraph Relational Reasoning Buzhen Huang Jingyi Ju Zhihao Li Yangang Wang 3DH 35 12 0 30 Aug 2023
GNNPipe: Scaling Deep GNN Training with Pipelined Model Parallelism Jingji Chen Zhuoming Chen Xuehai Qian GNN AI4CE 33 3 0 19 Aug 2023
Structure-Aware DropEdge Towards Deep Graph Convolutional Networks Jiaqi Han Wen-bing Huang Yu Rong Tingyang Xu Gang Hua Junzhou Huang 19 5 0 21 Jun 2023
Towards Deep Attention in Graph Neural Networks: Problems and Remedies Soo Yong Lee Fanchen Bu Jaemin Yoo Kijung Shin GNN 15 30 0 04 Jun 2023
Auto-Differentiation of Relational Computations for Very Large Scale Machine Learning Yu-Shuen Tang Zhimin Ding Dimitrije Jankov Binhang Yuan Daniel Bourgeois C. Jermaine BDL 24 6 0 31 May 2023
Improving Expressivity of GNNs with Subgraph-specific Factor Embedded Normalization Kaixuan Chen Shunyu Liu Tongtian Zhu Tongya Zheng Haofei Zhang Zunlei Feng Jingwen Ye Mingli Song 42 14 0 31 May 2023
Reversible and irreversible bracket-based dynamics for deep graph neural networks A. Gruber Kookjin Lee N. Trask AI4CE 25 9 0 24 May 2023
A Survey on Oversmoothing in Graph Neural Networks T. Konstantin Rusch Michael M. Bronstein Siddhartha Mishra 26 185 0 20 Mar 2023
Data-centric Artificial Intelligence: A Survey Daochen Zha Zaid Pervaiz Bhat Kwei-Herng Lai Fan Yang Zhimeng Jiang Shaochen Zhong Xia Hu 18 192 0 17 Mar 2023
Framelet Message Passing Xinliang Liu Bingxin Zhou Chutian Zhang Yu Guang Wang 28 5 0 28 Feb 2023
Reducing Over-smoothing in Graph Neural Networks Using Relational Embeddings Yeskendir Koishekenov 19 2 0 07 Jan 2023
On the Trade-off between Over-smoothing and Over-squashing in Deep Graph Neural Networks Jhony H. Giraldo Konstantinos Skianis T. Bouwmans Fragkiskos D. Malliaros 21 45 0 05 Dec 2022
Graph Convolutional Neural Networks with Diverse Negative Samples via Decomposed Determinant Point Processes Wei Duan Junyu Xuan Maoying Qiao Jie Lu 28 8 0 05 Dec 2022
Towards Training GNNs using Explanation Directed Message Passing V. Giunchiglia Chirag Varun Shukla Guadalupe Gonzalez Chirag Agarwal 27 7 0 30 Nov 2022
Mitigating Relational Bias on Knowledge Graphs Yu-Neng Chuang Kwei-Herng Lai Ruixiang Tang Mengnan Du Chia-Yuan Chang Na Zou Xia Hu FaML 17 5 0 26 Nov 2022
Tired of Over-smoothing? Stress Graph Drawing Is All You Need! Xue Li Yuanzhi Cheng 19 0 0 19 Nov 2022
Gradient Imitation Reinforcement Learning for General Low-Resource Information Extraction Xuming Hu Shiao Meng Chenwei Zhang Xiangli Yang Lijie Wen Irwin King Philip S. Yu 52 0 0 11 Nov 2022
QuanGCN: Noise-Adaptive Training for Robust Quantum Graph Convolutional Networks Kaixiong Zhou Zhenyu (Allen) Zhang Sheng-Wei Chen Tianlong Chen Xiao Huang Zhangyang Wang Xia Hu GNN 30 2 0 09 Nov 2022
Old can be Gold: Better Gradient Flow can Make Vanilla-GCNs Great Again Ajay Jaiswal Peihao Wang Tianlong Chen Justin F. Rousseau Ying Ding Zhangyang Wang 35 10 0 14 Oct 2022
A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking Keyu Duan Zirui Liu Peihao Wang Wenqing Zheng Kaixiong Zhou Tianlong Chen Xia Hu Zhangyang Wang GNN 41 57 0 14 Oct 2022
Graph Neural Network Surrogate for Seismic Reliability Analysis of Highway Bridge Systems Tong Liu Hadi Meidani 25 10 0 12 Oct 2022
Deep Learning-Derived Optimal Aviation Strategies to Control Pandemics S. Rizvi Akash Awasthi Maria J. Peláez Zhihui Wang V. Cristini Hien Nguyen P. Dogra 13 1 0 12 Oct 2022