Dirichlet Energy Constrained Learning for Deep Graph Neural Networks

6 July 2021

Daochen Zha

Papers citing "Dirichlet Energy Constrained Learning for Deep Graph Neural Networks"

50 / 71 papers shown

Title
Network-wide Freeway Traffic Estimation Using Sparse Sensor Data: A Dirichlet Graph Auto-Encoder Approach Qishen Zhou Yifan Zhang Michail A. Makridis Anastasios Kouvelas Yibing Wang Simon Hu 52 0 0 20 Mar 2025
Enhanced Soups for Graph Neural Networks Joseph Zuber Aishwarya Sarkar Joseph Jennings Ali Jannesari 47 0 0 14 Mar 2025
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
What makes a good feedforward computational graph? Alex Vitvitskyi J. G. Araújo Marc Lackenby Petar Velickovic 85 1 0 10 Feb 2025
Resolving Oversmoothing with Opinion Dissensus Keqin Wang Yulong Yang Ishan Saha Christine Allen-Blanchette 60 1 0 31 Jan 2025
A General Recipe for Contractive Graph Neural Networks -- Technical Report Maya Bechler-Speicher Moshe Eliasof 36 0 0 04 Nov 2024
Reducing Oversmoothing through Informed Weight Initialization in Graph Neural Networks Dimitrios Kelesis Dimitris Fotakis G. Paliouras 39 0 0 31 Oct 2024
Learning to Control the Smoothness of Graph Convolutional Network Features Shih-Hsin Wang Justin Baker Cory Hauck Bao Wang 38 0 0 18 Oct 2024
Partially Trained Graph Convolutional Networks Resist Oversmoothing Dimitrios Kelesis Dimitris Fotakis G. Paliouras SSL 18 0 0 17 Oct 2024
Preventing Representational Rank Collapse in MPNNs by Splitting the Computational Graph Andreas Roth Franka Bause Nils M. Kriege Thomas Liebig 35 3 0 17 Sep 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
Beyond Over-smoothing: Uncovering the Trainability Challenges in Deep Graph Neural Networks Jie Peng Runlin Lei Zhewei Wei 33 5 0 07 Aug 2024
Dirac--Bianconi Graph Neural Networks -- Enabling Non-Diffusive Long-Range Graph Predictions Christian Nauck R. Gorantla M. Lindner Konstantin Schurholt Antonia S. J. S. Mey Frank Hellmann AI4CE 50 2 0 17 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
Global-Local Graph Neural Networks for Node-Classification Moshe Eliasof Eran Treister 41 3 0 16 Jun 2024
Continuous Geometry-Aware Graph Diffusion via Hyperbolic Neural PDE Jiaxu Liu Xinping Yi Sihao Wu Xiangyu Yin Tianle Zhang Xiaowei Huang Shi Jin 40 0 0 03 Jun 2024
Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning on Heterophilic Graphs Langzhang Liang Sunwoo Kim Kijung Shin Zenglin Xu Shirui Pan Yuan Qi 37 3 0 31 May 2024
FlexiDrop: Theoretical Insights and Practical Advances in Random Dropout Method on GNNs Zhiheng Zhou Sihao Liu Weichen Zhao 24 0 0 30 May 2024
SmoothGNN: Smoothing-based GNN for Unsupervised Node Anomaly Detection Xiangyu Dong Xing Zhang Yanni Sun Lei Chen Mingxuan Yuan Sibo Wang 32 1 0 27 May 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
How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashing Keke Huang Yu Guang Wang Ming Li Pietro Lió 46 21 0 21 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
Spectral Graph Pruning Against Over-Squashing and Over-Smoothing Adarsh Jamadandi Celia Rubio-Madrigal R. Burkholz 42 1 0 06 Apr 2024
GTC: GNN-Transformer Co-contrastive Learning for Self-supervised Heterogeneous Graph Representation Yundong Sun Dongjie Zhu Yansong Wang Zhaoshuo Tian ViT SSL 38 13 0 22 Mar 2024
BloomGML: Graph Machine Learning through the Lens of Bilevel Optimization Amber Yijia Zheng Tong He Yixuan Qiu Minjie Wang David Wipf 36 2 0 07 Mar 2024
Entropy Aware Message Passing in Graph Neural Networks Philipp Nazari Oliver Lemke Davide Guidobene Artiom Gesp 33 0 0 07 Mar 2024
Simplified PCNet with Robustness Bingheng Li Xuanting Xie Haoxiang Lei Ruiyi Fang Zhao Kang 37 5 0 06 Mar 2024
Investigating Out-of-Distribution Generalization of GNNs: An Architecture Perspective Kai Guo Hongzhi Wen Wei Jin Yaming Guo Jiliang Tang Yi Chang OOD AI4CE 19 3 0 13 Feb 2024
Masked Graph Autoencoder with Non-discrete Bandwidths Zi-qiang Zhao Yuhua Li Yixiong Zou Jiliang Tang Ruixuan Li 27 10 0 06 Feb 2024
PC-Conv: Unifying Homophily and Heterophily with Two-fold Filtering Bingheng Li Erlin Pan Zhao Kang 24 31 0 22 Dec 2023
An Effective Universal Polynomial Basis for Spectral Graph Neural Networks Keke Huang Pietro Lió 16 1 0 30 Nov 2023
Dirichlet Energy Enhancement of Graph Neural Networks by Framelet Augmentation Jialin Chen Yuelin Wang Cristian Bodnar Rex Ying Pietro Lió Yu Guang Wang 29 10 0 09 Nov 2023
D4Explainer: In-Distribution GNN Explanations via Discrete Denoising Diffusion Jialin Chen Shirley Wu Abhijit Gupta Rex Ying DiffM 42 4 0 30 Oct 2023
DeepHGCN: Toward Deeper Hyperbolic Graph Convolutional Networks Jiaxu Liu Xinping Yi Xiaowei Huang 38 2 0 03 Oct 2023
Rank Collapse Causes Over-Smoothing and Over-Correlation in Graph Neural Networks Andreas Roth Thomas Liebig 43 12 0 31 Aug 2023
Anomaly Detection in Networks via Score-Based Generative Models Dmitrii Gavrilev Evgeny Burnaev 22 3 0 27 Jun 2023
Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication A. Jaiswal Shiwei Liu Tianlong Chen Ying Ding Zhangyang Wang GNN 42 5 0 18 Jun 2023
Towards Label Position Bias in Graph Neural Networks Haoyu Han Xiaorui Liu Feng Shi MohamadAli Torkamani Charu C. Aggarwal Jiliang Tang 34 4 0 25 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
Steering Graph Neural Networks with Pinning Control Acong Zhang P. Li Guanrong Chen LLMSV 29 0 0 02 Mar 2023
Towards Training GNNs using Explanation Directed Message Passing V. Giunchiglia Chirag Varun Shukla Guadalupe Gonzalez Chirag Agarwal 30 7 0 30 Nov 2022
Every Node Counts: Improving the Training of Graph Neural Networks on Node Classification Moshe Eliasof E. Haber Eran Treister GNN 25 0 0 29 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
Improving Graph Neural Networks with Learnable Propagation Operators Moshe Eliasof Lars Ruthotto Eran Treister 34 20 0 31 Oct 2022