Predict then Propagate: Graph Neural Networks meet Personalized PageRank

14 October 2018

Johannes Klicpera

Aleksandar Bojchevski

Stephan Günnemann

GNN

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Papers citing "Predict then Propagate: Graph Neural Networks meet Personalized PageRank"

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SAGMAN: Stability Analysis of Graph Neural Networks on the Manifolds Wuxinlin Cheng Chenhui Deng Ali Aghdaei Zhiru Zhang Zhuo Feng AAML 23 1 0 13 Feb 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 11 3 0 13 Feb 2024
Rethinking Node-wise Propagation for Large-scale Graph Learning Xunkai Li Jingyuan Ma Zhengyu Wu Daohan Su Wentao Zhang Ronghua Li Guoren Wang AI4CE 17 11 0 09 Feb 2024
Rethinking Propagation for Unsupervised Graph Domain Adaptation Meihan Liu Zeyu Fang Zhen Zhang Ming Gu Sheng Zhou Xin Eric Wang Jiajun Bu AI4CE 31 14 0 08 Feb 2024
Navigating Complexity: Toward Lossless Graph Condensation via Expanding Window Matching Yuchen Zhang Tianle Zhang Kai Wang Ziyao Guo Yuxuan Liang Xavier Bresson Wei Jin Yang You 28 23 0 07 Feb 2024
Two Trades is not Baffled: Condensing Graph via Crafting Rational Gradient Matching Tianle Zhang Yuchen Zhang Kun Wang Kai Wang Beining Yang Kaipeng Zhang Wenqi Shao Ping Liu Joey Tianyi Zhou Yang You DD 63 13 0 07 Feb 2024
Meet JEANIE: a Similarity Measure for 3D Skeleton Sequences via Temporal-Viewpoint Alignment Lei Wang Jun Liu Liang Zheng Tom Gedeon Piotr Koniusz 25 9 0 07 Feb 2024
FairWire: Fair Graph Generation O. D. Kose Yanning Shen 21 3 0 06 Feb 2024
Understanding and Guiding Weakly Supervised Entity Alignment with Potential Isomorphism Propagation Yuanyi Wang Wei Tang Haifeng Sun Zirui Zhuang Xiaoyuan Fu Jingyu Wang Qi Qi Jianxin Liao 16 1 0 05 Feb 2024
EXGC: Bridging Efficiency and Explainability in Graph Condensation Junfeng Fang Xinglin Li Yongduo Sui Yuan Gao Guibin Zhang Kun Wang Xiang Wang Xiangnan He DD 51 18 0 05 Feb 2024
Active Learning for Graphs with Noisy Structures Hongliang Chi Cong Qi Suhang Wang Yao Ma 25 3 0 04 Feb 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 46 25 0 03 Feb 2024
Precedence-Constrained Winter Value for Effective Graph Data Valuation Hongliang Chi Wei Jin Charu C. Aggarwal Yao Ma 34 3 0 02 Feb 2024
DGNN: Decoupled Graph Neural Networks with Structural Consistency between Attribute and Graph Embedding Representations Jinlu Wang Jipeng Guo Yanfeng Sun Junbin Gao Shaofan Wang Yachao Yang Baocai Yin AI4CE 21 2 0 28 Jan 2024
Improving Expressive Power of Spectral Graph Neural Networks with Eigenvalue Correction Kangkang Lu Yanhua Yu Hao Fei Xuan Li Zixuan Yang Zirui Guo Meiyu Liang Mengran Yin Tat-Seng Chua 11 2 0 28 Jan 2024
Cross-Space Adaptive Filter: Integrating Graph Topology and Node Attributes for Alleviating the Over-smoothing Problem Chen Huang Haoyang Li Yifan Zhang Wenqiang Lei Jiancheng Lv 25 3 0 26 Jan 2024
Topology-aware Embedding Memory for Continual Learning on Expanding Networks Xikun Zhang Dongjin Song Yixin Chen Dacheng Tao 14 3 0 24 Jan 2024
EMP: Effective Multidimensional Persistence for Graph Representation Learning I. Segovia-Dominguez Yuzhou Chen Cüneyt Gürcan Akçora Zhiwei Zhen Murat Kantarcioglu Yulia R. Gel Baris Coskunuzer 51 4 0 24 Jan 2024
Learning to Approximate Adaptive Kernel Convolution on Graphs Jaeyoon Sim Sooyeon Jeon Injun Choi Guorong Wu Won Hwa Kim 11 3 0 22 Jan 2024
AdaFGL: A New Paradigm for Federated Node Classification with Topology Heterogeneity Xunkai Li Zhengyu Wu Wentao Zhang Henan Sun Ronghua Li Guoren Wang FedML 31 7 0 22 Jan 2024
Infinite-Horizon Graph Filters: Leveraging Power Series to Enhance Sparse Information Aggregation Ruizhe Zhang Xinke Jiang Yuchen Fang Jiayuan Luo Yongxin Xu Yichen Zhu Xu Chu Junfeng Zhao Yasha Wang 21 1 0 18 Jan 2024
Rethinking Spectral Graph Neural Networks with Spatially Adaptive Filtering Jingwei Guo Kaizhu Huang Xinping Yi Zixian Su Rui Zhang 24 3 0 17 Jan 2024
Consistency of semi-supervised learning, stochastic tug-of-war games, and the p-Laplacian Jeff Calder Nadejda Drenska 12 1 0 15 Jan 2024
Few-Shot Causal Representation Learning for Out-of-Distribution Generalization on Heterogeneous Graphs Pengfei Ding Yan Wang Guanfeng Liu Nan Wang Xiaofang Zhou OODD OOD 18 2 0 07 Jan 2024
View-based Explanations for Graph Neural Networks Tingyang Chen Dazhuo Qiu Yinghui Wu Arijit Khan Xiangyu Ke Yunjun Gao 33 9 0 04 Jan 2024
Graph Elimination Networks Shuo Wang Ge Cheng Yun Zhang AI4CE GNN 16 0 0 02 Jan 2024
Graph Learning in 4D: a Quaternion-valued Laplacian to Enhance Spectral GCNs Stefano Fiorini Stefano Coniglio Michele Ciavotta Enza Messina GNN 18 5 0 28 Dec 2023
FCDNet: Frequency-Guided Complementary Dependency Modeling for Multivariate Time-Series Forecasting Weijun Chen Heyuan Wang Ye Tian Shijie Guan Ning Liu AI4TS 17 1 0 27 Dec 2023
Joint Learning Neuronal Skeleton and Brain Circuit Topology with Permutation Invariant Encoders for Neuron Classification Minghui Liao Guojia Wan Bo Du 17 2 0 22 Dec 2023
NodeMixup: Tackling Under-Reaching for Graph Neural Networks Weigang Lu Ziyu Guan Wei Zhao Yaming Yang Long Jin 27 11 0 20 Dec 2023
Graph Transformers for Large Graphs Vijay Prakash Dwivedi Yozen Liu A. Luu Xavier Bresson Neil Shah Tong Zhao GNN 18 6 0 18 Dec 2023
LightGCN: Evaluated and Enhanced David Murphy Luca Pantea Andrei Blahovici GNN 11 0 0 17 Dec 2023
p-Laplacian Adaptation for Generative Pre-trained Vision-Language Models Haoyuan Wu Xinyun Zhang Peng Xu Peiyu Liao Xufeng Yao Bei Yu VLM 19 0 0 17 Dec 2023
Graph Neural Networks with Diverse Spectral Filtering Jingwei Guo Kaizhu Huang Xinping Yi Rui Zhang 32 11 0 14 Dec 2023
A Generalized Neural Diffusion Framework on Graphs Yibo Li Xiao Wang Hongrui Liu Chuan Shi DiffM AI4CE 17 15 0 14 Dec 2023
Polynomial-based Self-Attention for Table Representation learning Jayoung Kim Yehjin Shin Jeongwhan Choi Hyowon Wi Noseong Park LMTD 17 1 0 12 Dec 2023
$Poisoning $\times$ Evasion: Symbiotic Adversarial Robustness for Graph Neural Networks$ Poisoning $\times$ Evasion: Symbiotic Adversarial Robustness for Graph Neural Networks Ege Erdogan Simon Geisler Stephan Günnemann AAML 11 0 0 09 Dec 2023
Efficient Large Language Models Fine-Tuning On Graphs Rui Xue Xipeng Shen Ruozhou Yu Xiaorui Liu 20 4 0 07 Dec 2023
Breaking the Entanglement of Homophily and Heterophily in Semi-supervised Node Classification Henan Sun Xunkai Li Zhengyu Wu Daohan Su Ronghua Li Guoren Wang 27 12 0 07 Dec 2023
Adaptive Dependency Learning Graph Neural Networks Abishek Sriramulu Nicolas Fourrier Christoph Bergmeir AI4TS AI4CE 16 21 0 06 Dec 2023
The Self-Loop Paradox: Investigating the Impact of Self-Loops on Graph Neural Networks Moritz Lampert Ingo Scholtes GNN SSL 12 4 0 04 Dec 2023
An Effective Universal Polynomial Basis for Spectral Graph Neural Networks Keke Huang Pietro Lió 16 1 0 30 Nov 2023
Propagate & Distill: Towards Effective Graph Learners Using Propagation-Embracing MLPs Yong-Min Shin Won-Yong Shin 21 1 0 29 Nov 2023
Robust Graph Neural Networks via Unbiased Aggregation Ruiqi Feng Zhichao Hou Tyler Derr Xiaorui Liu 16 0 0 25 Nov 2023
BHGNN-RT: Network embedding for directed heterogeneous graphs Xiyang Sun F. Komaki 24 1 0 24 Nov 2023
AdaMedGraph: Adaboosting Graph Neural Networks for Personalized Medicine Jie Lian Xufang Luo Caihua Shan Dongqi Han V. Vardhanabhuti Dongsheng Li 11 0 0 24 Nov 2023
Unveiling the Unseen Potential of Graph Learning through MLPs: Effective Graph Learners Using Propagation-Embracing MLPs Yong-Min Shin Won-Yong Shin 11 1 0 20 Nov 2023
Benchmarking Machine Learning Models for Quantum Error Correction Yue Zhao 8 1 0 18 Nov 2023
Reviewing Developments of Graph Convolutional Network Techniques for Recommendation Systems Haojun Zhu Vikram Kapoor Priya Sharma GNN 12 0 0 10 Nov 2023
Improvements on Uncertainty Quantification for Node Classification via Distance-Based Regularization Russell Hart Linlin Yu Yifei Lou Feng Chen UQCV 16 4 0 10 Nov 2023