Graph Neural Networks Inspired by Classical Iterative Algorithms

10 March 2021

Papers citing "Graph Neural Networks Inspired by Classical Iterative Algorithms"

50 / 54 papers shown

Title
GRAIN: Multi-Granular and Implicit Information Aggregation Graph Neural Network for Heterophilous Graphs Songwei Zhao Yuan Jiang Zijing Zhang Yang Yu Hechang Chen 19 0 0 09 Apr 2025
Hyperspherical Energy Transformer with Recurrent Depth Yunzhe Hu Difan Zou Dong Xu 43 0 0 17 Feb 2025
Efficient Link Prediction via GNN Layers Induced by Negative Sampling Yuxin Wang Xiannian Hu Quan Gan Xuanjing Huang Xipeng Qiu David Wipf 58 4 0 31 Dec 2024
An In-depth Investigation of Sparse Rate Reduction in Transformer-like Models Yunzhe Hu Difan Zou Dong Xu 71 1 0 26 Nov 2024
Neural Message Passing Induced by Energy-Constrained Diffusion Qitian Wu David Wipf Junchi Yan DiffM 52 1 0 13 Sep 2024
Unveiling the Hidden Structure of Self-Attention via Kernel Principal Component Analysis R. Teo Tan M. Nguyen 45 4 0 19 Jun 2024
Interpretable Lightweight Transformer via Unrolling of Learned Graph Smoothness Priors Tam Thuc Do Parham Eftekhar Seyed Alireza Hosseini Gene Cheung Philip A. Chou 29 0 0 06 Jun 2024
Graph Adversarial Diffusion Convolution Songtao Liu Jinghui Chen Tianfan Fu Lu Lin Marinka Zitnik Dinghao Wu DiffM 39 2 0 04 Jun 2024
Co-Representation Neural Hypergraph Diffusion for Edge-Dependent Node Classification Yijia Zheng M. Worring DiffM 45 1 0 23 May 2024
HERTA: A High-Efficiency and Rigorous Training Algorithm for Unfolded Graph Neural Networks Yongyi Yang Jiaming Yang Wei Hu Michal Dereziñski 48 0 0 26 Mar 2024
BloomGML: Graph Machine Learning through the Lens of Bilevel Optimization Amber Yijia Zheng Tong He Yixuan Qiu Minjie Wang David Wipf 33 2 0 07 Mar 2024
Simplified PCNet with Robustness Bingheng Li Xuanting Xie Haoxiang Lei Ruiyi Fang Zhao Kang 37 5 0 06 Mar 2024
Position: Graph Foundation Models are Already Here Haitao Mao Zhikai Chen Wenzhuo Tang Jianan Zhao Yao Ma Tong Zhao Neil Shah Mikhail Galkin Jiliang Tang AI4CE 59 26 0 03 Feb 2024
PC-Conv: Unifying Homophily and Heterophily with Two-fold Filtering Bingheng Li Erlin Pan Zhao Kang 19 31 0 22 Dec 2023
Robust Graph Neural Networks via Unbiased Aggregation Ruiqi Feng Zhichao Hou Tyler Derr Xiaorui Liu 26 0 0 25 Nov 2023
MuseGNN: Forming Scalable, Convergent GNN Layers that Minimize a Sampling-Based Energy Haitian Jiang Renjie Liu Xiao Yan Zhenkun Cai Minjie Wang David Wipf Minjie Wang David Wipf GNN AI4CE 21 3 0 19 Oct 2023
How Graph Neural Networks Learn: Lessons from Training Dynamics Chenxiao Yang Qitian Wu David Wipf Ruoyu Sun Junchi Yan AI4CE GNN 22 1 0 08 Oct 2023
TouchUp-G: Improving Feature Representation through Graph-Centric Finetuning Jing Zhu Xiang Song V. Ioannidis Danai Koutra Christos Faloutsos 56 13 0 25 Sep 2023
From Cluster Assumption to Graph Convolution: Graph-based Semi-Supervised Learning Revisited Zheng Wang H. Ding L. Pan Jianhua Li Zhiguo Gong Philip S. Yu GNN 21 5 0 24 Sep 2023
Spatial Heterophily Aware Graph Neural Networks Congxi Xiao Jingbo Zhou Jizhou Huang Tong Bill Xu Hui Xiong 26 5 0 21 Jun 2023
From Hypergraph Energy Functions to Hypergraph Neural Networks Yuxin Wang Quan Gan Xipeng Qiu Xuanjing Huang David Wipf GNN 16 13 0 16 Jun 2023
Spectral Heterogeneous Graph Convolutions via Positive Noncommutative Polynomials Mingguo He Zhewei Wei Shi Feng Zhengjie Huang Weibin Li Yu Sun Dianhai Yu 21 6 0 31 May 2023
LON-GNN: Spectral GNNs with Learnable Orthonormal Basis Qian Tao Zhen Wang Wenyuan Yu Yaliang Li Zhewei Wei 27 5 0 24 Mar 2023
Framelet Message Passing Xinliang Liu Bingxin Zhou Chutian Zhang Yu Guang Wang 25 5 0 28 Feb 2023
G-Signatures: Global Graph Propagation With Randomized Signatures Bernhard Schafl Lukas Gruber Johannes Brandstetter Sepp Hochreiter 19 2 0 17 Feb 2023
LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation Rui Xue Haoyu Han MohamadAli Torkamani Jian Pei Xiaorui Liu GNN 31 19 0 03 Feb 2023
DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion Qitian Wu Chenxiao Yang Wen-Long Zhao Yixuan He David Wipf Junchi Yan DiffM 19 82 0 23 Jan 2023
Beyond Graph Convolutional Network: An Interpretable Regularizer-centered Optimization Framework Shiping Wang Zhihao Wu Yuhong Chen Yongzhe Chen GNN BDL 26 13 0 11 Jan 2023
MECCH: Metapath Context Convolution-based Heterogeneous Graph Neural Networks Xinyu Fu Irwin King 27 15 0 23 Nov 2022
ASGNN: Graph Neural Networks with Adaptive Structure Zepeng Zhang Songtao Lu Zengfeng Huang Ziping Zhao AAML 46 1 0 03 Oct 2022
Alternating Differentiation for Optimization Layers Haixiang Sun Ye Shi Jingya Wang H. Tuan H. Vincent Poor Dacheng Tao ODL 35 14 0 03 Oct 2022
How Powerful is Implicit Denoising in Graph Neural Networks Songtao Liu Rex Ying Hanze Dong Lu Lin Jinghui Chen Di Wu GNN AI4CE 22 3 0 29 Sep 2022
Equivariant Hypergraph Diffusion Neural Operators Peihao Wang Shenghao Yang Yunyu Liu Zhangyang Wang Pan Li DiffM 22 33 0 14 Jul 2022
Optimization-Induced Graph Implicit Nonlinear Diffusion Qi Chen Yifei Wang Yisen Wang Jiansheng Yang Zhouchen Lin DiffM 48 32 0 29 Jun 2022
Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks Hongjoon Ahn You‐Jun Yang Quan Gan Taesup Moon David Wipf 33 25 0 22 Jun 2022
A Robust Stacking Framework for Training Deep Graph Models with Multifaceted Node Features Jiuhai Chen Jonas W. Mueller V. Ioannidis Tom Goldstein David Wipf 24 2 0 16 Jun 2022
Long Range Graph Benchmark Vijay Prakash Dwivedi Ladislav Rampášek Mikhail Galkin Alipanah Parviz Guy Wolf A. Luu Dominique Beaini 26 195 0 16 Jun 2022
Towards Understanding Graph Neural Networks: An Algorithm Unrolling Perspective Zepeng Zhang Ziping Zhao AI4CE 27 4 0 09 Jun 2022
EvenNet: Ignoring Odd-Hop Neighbors Improves Robustness of Graph Neural Networks Runlin Lei Zhen Wang Yaliang Li Bolin Ding Zhewei Wei AAML 21 42 0 27 May 2022
Transformers from an Optimization Perspective Yongyi Yang Zengfeng Huang David Wipf 39 24 0 27 May 2022
Ensemble Multi-Relational Graph Neural Networks Yuling Wang Haonan Xu Yanhua Yu Mengdi Zhang Zhenhao Li Yuji Yang Wei Yu Wu 28 7 0 24 May 2022
Finding Global Homophily in Graph Neural Networks When Meeting Heterophily Xiang Li Renyu Zhu Yao Cheng Caihua Shan Siqiang Luo Dongsheng Li Wei Qian 15 181 0 15 May 2022
Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited Mingguo He Zhewei Wei Ji-Rong Wen GNN 19 100 0 04 Feb 2022
MGNN: Graph Neural Networks Inspired by Distance Geometry Problem Guanyu Cui Zhewei Wei 23 7 0 31 Jan 2022
Combining Optimal Path Search With Task-Dependent Learning in a Neural Network Tomas Kulvicius M. Tamosiunaite F. Worgotter 25 1 0 26 Jan 2022
A Piece-wise Polynomial Filtering Approach for Graph Neural Networks Vijay Lingam C. Ekbote Manan Sharma Rahul Ragesh Arun Shankar Iyer Sundararajan Sellamanickam 28 6 0 07 Dec 2021
Implicit vs Unfolded Graph Neural Networks Yongyi Yang Tang Liu Yangkun Wang Zengfeng Huang David Wipf 44 15 0 12 Nov 2021
Does your graph need a confidence boost? Convergent boosted smoothing on graphs with tabular node features Jiuhai Chen Jonas W. Mueller V. Ioannidis Soji Adeshina Yangkun Wang Tom Goldstein David Wipf 27 12 0 26 Oct 2021
Why Propagate Alone? Parallel Use of Labels and Features on Graphs Yangkun Wang Jiarui Jin Weinan Zhang Yongyi Yang Jiuhai Chen Quan Gan Yong Yu Zheng-Wei Zhang Zengfeng Huang David Wipf AAML 55 12 0 14 Oct 2021
Is Attention Better Than Matrix Decomposition? Zhengyang Geng Meng-Hao Guo Hongxu Chen Xia Li Ke Wei Zhouchen Lin 56 137 0 09 Sep 2021