Diffusion Improves Graph Learning

28 October 2019

Stephan Günnemann

Papers citing "Diffusion Improves Graph Learning"

50 / 344 papers shown

Title
Temporal Graph Rewiring with Expander Graphs Katarina Petrović Shenyang Huang Farimah Poursafaei Petar Velickovic AI4CE 45 4 0 04 Jun 2024
Graph Adversarial Diffusion Convolution Songtao Liu Jinghui Chen Tianfan Fu Lu Lin Marinka Zitnik Dinghao Wu DiffM 26 2 0 04 Jun 2024
Learning on Large Graphs using Intersecting Communities Ben Finkelshtein .Ismail .Ilkan Ceylan Michael M. Bronstein Ron Levie GNN 30 5 0 31 May 2024
Towards Deeper Understanding of PPR-based Embedding Approaches: A Topological Perspective Xingyi Zhang Zixuan Weng Sibo Wang 28 4 0 30 May 2024
Spatio-Spectral Graph Neural Networks Simon Geisler Arthur Kosmala Daniel Herbst Stephan Günnemann 45 8 0 29 May 2024
Calibrated Dataset Condensation for Faster Hyperparameter Search Mucong Ding Yuancheng Xu Tahseen Rabbani Xiaoyu Liu Brian J Gravelle Teresa M. Ranadive Tai-Ching Tuan Furong Huang DD 32 0 0 27 May 2024
Spectral Greedy Coresets for Graph Neural Networks Mucong Ding Yinhan He Jundong Li Furong Huang 23 3 0 27 May 2024
Probabilistic Graph Rewiring via Virtual Nodes Chendi Qian Andrei Manolache Christopher Morris Mathias Niepert AI4CE 38 3 0 27 May 2024
Rethinking and Accelerating Graph Condensation: A Training-Free Approach with Class Partition Xin Gao Tong Chen Wentao Zhang Junliang Yu Guanhua Ye Quoc Viet Hung Nguyen 34 7 0 22 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 35 17 0 21 May 2024
Towards Graph Contrastive Learning: A Survey and Beyond Wei Ju Yifan Wang Yifang Qin Zhengyan Mao Zhiping Xiao ... Dongjie Wang Qingqing Long Siyu Yi Xiao Luo Ming Zhang 47 12 0 20 May 2024
A Comprehensive Survey on Data Augmentation Zaitian Wang Pengfei Wang Kunpeng Liu Pengyang Wang Yanjie Fu Chang-Tien Lu Charu Aggarwal Jian Pei Yuanchun Zhou ViT 95 21 0 15 May 2024
Relating-Up: Advancing Graph Neural Networks through Inter-Graph Relationships Qi Zou Na Yu Daoliang Zhang Wei Zhang Rui Gao AI4CE 27 1 0 07 May 2024
ATNPA: A Unified View of Oversmoothing Alleviation in Graph Neural Networks Yufei Jin Xingquan Zhu 46 2 0 02 May 2024
CKGConv: General Graph Convolution with Continuous Kernels Liheng Ma Soumyasundar Pal Yitian Zhang Jiaming Zhou Yingxue Zhang Mark J. Coates 37 3 0 21 Apr 2024
Graph Neural Networks for Binary Programming Moshe Eliasof Eldad Haber GNN 27 0 0 07 Apr 2024
Spectral Graph Pruning Against Over-Squashing and Over-Smoothing Adarsh Jamadandi Celia Rubio-Madrigal R. Burkholz 40 1 0 06 Apr 2024
Convection-Diffusion Equation: A Theoretically Certified Framework for Neural Networks Tangjun Wang Chenglong Bao Zuoqiang Shi DiffM 36 0 0 23 Mar 2024
Graph Unitary Message Passing Haiquan Qiu Yatao Bian Quanming Yao 24 2 0 17 Mar 2024
Optimizing Polynomial Graph Filters: A Novel Adaptive Krylov Subspace Approach Keke Huang Wencai Cao Hoang Ta Xiaokui Xiao Pietro Lió 41 3 0 12 Mar 2024
A Survey of Graph Neural Networks in Real world: Imbalance, Noise, Privacy and OOD Challenges Wei Ju Siyu Yi Yifan Wang Zhiping Xiao Zhengyan Mao ... Senzhang Wang Xinwang Liu Xiao Luo Philip S. Yu Ming Zhang AI4CE 34 36 0 07 Mar 2024
Graph Parsing Networks Yunchong Song Siyuan Huang Xinbing Wang Cheng Zhou Zhouhan Lin GNN 32 3 0 22 Feb 2024
Any2Graph: Deep End-To-End Supervised Graph Prediction With An Optimal Transport Loss Paul Krzakala Junjie Yang Rémi Flamary Florence dÁlché-Buc Charlotte Laclau Matthieu Labeau OT 27 1 0 19 Feb 2024
PAC Learnability under Explanation-Preserving Graph Perturbations Xu Zheng Farhad Shirani Tianchun Wang Shouwei Gao Wenqian Dong Wei Cheng Dongsheng Luo 22 0 0 07 Feb 2024
Spectrally Transformed Kernel Regression Runtian Zhai Rattana Pukdee Roger Jin Maria-Florina Balcan Pradeep Ravikumar BDL 15 2 0 01 Feb 2024
Graph Contrastive Learning with Cohesive Subgraph Awareness Yucheng Wu Leye Wang Xiao Han Han-Jia Ye 19 3 0 31 Jan 2024
Manifold GCN: Diffusion-based Convolutional Neural Network for Manifold-valued Graphs M. Hanik Gabriele Steidl C. V. Tycowicz GNN MedIm 19 3 0 25 Jan 2024
Learning to Approximate Adaptive Kernel Convolution on Graphs Jaeyoon Sim Sooyeon Jeon Injun Choi Guorong Wu Won Hwa Kim 16 3 0 22 Jan 2024
On The Temporal Domain of Differential Equation Inspired Graph Neural Networks Moshe Eliasof E. Haber Eran Treister Carola-Bibiane Schönlieb AI4CE 19 2 0 20 Jan 2024
Multi-relational Graph Diffusion Neural Network with Parallel Retention for Stock Trends Classification Zinuo You Pengju Zhang Jin Zheng John Cartlidge AIFin DiffM 13 5 0 05 Jan 2024
DGDNN: Decoupled Graph Diffusion Neural Network for Stock Movement Prediction Zinuo You Zijian Shi Hongbo Bo John Cartlidge Li Zhang Yan Ge AIFin DiffM 18 2 0 03 Jan 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 50 7 0 27 Dec 2023
Diffusion Maps for Signal Filtering in Graph Learning Todd Hildebrant DiffM 13 0 0 22 Dec 2023
PC-Conv: Unifying Homophily and Heterophily with Two-fold Filtering Bingheng Li Erlin Pan Zhao Kang 14 30 0 22 Dec 2023
Degree-based stratification of nodes in Graph Neural Networks Ameen Ali Hakan Çevikalp Lior Wolf 28 0 0 16 Dec 2023
Neural Gaussian Similarity Modeling for Differential Graph Structure Learning Xiaolong Fan Maoguo Gong Yue Wu Zedong Tang Jie Liu 25 0 0 15 Dec 2023
Simplicial Representation Learning with Neural $k$ -Forms Kelly Maggs Celia Hacker Bastian Alexander Rieck AI4CE 25 10 0 13 Dec 2023
The Graph Lottery Ticket Hypothesis: Finding Sparse, Informative Graph Structure Anton Tsitsulin Bryan Perozzi 24 5 0 08 Dec 2023
Graph Convolutions Enrich the Self-Attention in Transformers! Jeongwhan Choi Hyowon Wi Jayoung Kim Yehjin Shin Kookjin Lee Nathaniel Trask Noseong Park 25 4 0 07 Dec 2023
An Effective Universal Polynomial Basis for Spectral Graph Neural Networks Keke Huang Pietro Lió 16 1 0 30 Nov 2023
AMES: A Differentiable Embedding Space Selection Framework for Latent Graph Inference Yuan Lu Haitz Sáez de Ocáriz Borde Pietro Lio' 11 2 0 20 Nov 2023
Benchmarking Machine Learning Models for Quantum Error Correction Yue Zhao 13 1 0 18 Nov 2023
Classification of developmental and brain disorders via graph convolutional aggregation Ibrahim Salim A. B. Hamza MedIm 11 11 0 13 Nov 2023
Exposition on over-squashing problem on GNNs: Current Methods, Benchmarks and Challenges Dai Shi Andi Han Lequan Lin Yi Guo Junbin Gao 47 11 0 13 Nov 2023
Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel Xuan Li Zhanke Zhou Jiangchao Yao Yu Rong Lu Zhang Bo Han 29 3 0 02 Nov 2023
Pattern formation in vector-valued phase fields under convex constraints O. Vantzos AI4CE 11 0 0 02 Nov 2023
Robust Graph Clustering via Meta Weighting for Noisy Graphs Hyeonsoo Jo Fanchen Bu Kijung Shin OOD NoLa 12 7 0 01 Nov 2023
A Quasi-Wasserstein Loss for Learning Graph Neural Networks Minjie Cheng Hongteng Xu 25 1 0 18 Oct 2023
PREM: A Simple Yet Effective Approach for Node-Level Graph Anomaly Detection Junjun Pan Yixin Liu Yizhen Zheng Shirui Pan 32 18 0 18 Oct 2023
Self-supervision meets kernel graph neural models: From architecture to augmentations Jiawang Dan Ruofan Wu Yunpeng Liu Baokun Wang Changhua Meng ... Tianyi Zhang Ningtao Wang Xin Fu Qi Li Weiqiang Wang SSL 23 1 0 17 Oct 2023