Revisiting Semi-Supervised Learning with Graph Embeddings

29 March 2016

Papers citing "Revisiting Semi-Supervised Learning with Graph Embeddings"

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Title
EdgePruner: Poisoned Edge Pruning in Graph Contrastive Learning Hiroya Kato Kento Hasegawa Seira Hidano Kazuhide Fukushima AAML 32 0 0 12 Dec 2023
ASWT-SGNN: Adaptive Spectral Wavelet Transform-based Self-Supervised Graph Neural Network Ruyue Liu Rong Yin Yong Liu Weiping Wang SSL 29 3 0 10 Dec 2023
Not All Negatives Are Worth Attending to: Meta-Bootstrapping Negative Sampling Framework for Link Prediction Yakun Wang Binbin Hu Shuo Yang Meiqi Zhu Qing Cui Qiyang Zhang Jun Zhou Guo Ye Huimei He 30 0 0 08 Dec 2023
Efficient Large Language Models Fine-Tuning On Graphs Rui Xue Xipeng Shen Ruozhou Yu Xiaorui Liu 35 3 0 07 Dec 2023
GraphMETRO: Mitigating Complex Graph Distribution Shifts via Mixture of Aligned Experts Shirley Wu Kaidi Cao Bruno Ribeiro James Zou J. Leskovec OOD 34 3 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 40 12 0 07 Dec 2023
Uncertainty in Graph Contrastive Learning with Bayesian Neural Networks Alexander M¨ollers Alexander Immer Elvin Isufi Vincent Fortuin SSL BDL UQCV 26 1 0 30 Nov 2023
On the Adversarial Robustness of Graph Contrastive Learning Methods Filippo Guerranti Zinuo Yi Anna Starovoit Rafiq Kamel Simon Geisler Stephan Günnemann AAML 41 2 0 29 Nov 2023
Propagate & Distill: Towards Effective Graph Learners Using Propagation-Embracing MLPs Yong-Min Shin Won-Yong Shin 29 1 0 29 Nov 2023
Effective Structural Encodings via Local Curvature Profiles Lukas Fesser Melanie Weber 38 3 0 24 Nov 2023
Unsupervised Graph Attention Autoencoder for Attributed Networks using K-means Loss Abdelfateh Bekkair Slimane Bellaouar Slimane Oulad-Naoui 21 0 0 21 Nov 2023
Content Augmented Graph Neural Networks Fatemeh Gholamzadeh Nasrabadi AmirHossein Kashani Pegah Zahedi M. H. Chehreghani 18 2 0 21 Nov 2023
A Survey of Graph Meets Large Language Model: Progress and Future Directions Yuhan Li Zhixun Li Peisong Wang Jia Li Xiangguo Sun Hongtao Cheng Jeffrey Xu Yu 53 56 0 21 Nov 2023
Unveiling the Unseen Potential of Graph Learning through MLPs: Effective Graph Learners Using Propagation-Embracing MLPs Yong-Min Shin Won-Yong Shin 21 1 0 20 Nov 2023
A Poincaré Inequality and Consistency Results for Signal Sampling on Large Graphs Thien Le Luana Ruiz Stefanie Jegelka 29 0 0 17 Nov 2023
Evaluating Neighbor Explainability for Graph Neural Networks Oscar Llorente Rana Fawzy Jared Keown Michal Horemuz Péter Vaderna Sándor Laki Roland Kotroczó Rita Csoma János Márk Szalai-Gindl 22 0 0 14 Nov 2023
Preserving Node-level Privacy in Graph Neural Networks Zihang Xiang Tianhao Wang Di Wang 32 6 0 12 Nov 2023
Greedy PIG: Adaptive Integrated Gradients Kyriakos Axiotis Sami Abu-El-Haija Lin Chen Matthew Fahrbach Gang Fu FAtt 26 0 0 10 Nov 2023
Dirichlet Energy Enhancement of Graph Neural Networks by Framelet Augmentation Jialin Chen Yuelin Wang Cristian Bodnar Rex Ying Pietro Lio Yu Guang Wang 42 10 0 09 Nov 2023
Information-Theoretic Generalization Bounds for Transductive Learning and its Applications Huayi Tang Yong Liu 62 1 0 08 Nov 2023
Prioritized Propagation in Graph Neural Networks Yao Cheng Minjie Chen Xiang Li Caihua Shan Ming Gao AI4CE 38 0 0 06 Nov 2023
Cooperative Network Learning for Large-Scale and Decentralized Graphs Qiang Wu Yiming Huang Yujie Zeng Yujie Teng Fang Zhou Linyuan Lu GNN FedML 37 0 0 03 Nov 2023
A Metadata-Driven Approach to Understand Graph Neural Networks Tinghong Li Qiaozhu Mei Jiaqi Ma AI4CE 31 5 0 30 Oct 2023
Curriculum Learning for Graph Neural Networks: Which Edges Should We Learn First Zhengwu Zhang Junxiang Wang Liang Zhao 47 13 0 28 Oct 2023
Rethinking Semi-Supervised Imbalanced Node Classification from Bias-Variance Decomposition Divin Yan Gengchen Wei Chen Yang Shengzhong Zhang Zengfeng Huang AI4CE 51 11 0 28 Oct 2023
Unleashing the potential of GNNs via Bi-directional Knowledge Transfer Shuai Zheng Zhizhe Liu Zhenfeng Zhu Xingxing Zhang Jianxin Li Yao-Min Zhao 38 0 0 26 Oct 2023
IntenDD: A Unified Contrastive Learning Approach for Intent Detection and Discovery Bhavuk Singhal Ashim Gupta P. ShivasankaranV Amrith Krishna 30 1 0 25 Oct 2023
Graph Agent: Explicit Reasoning Agent for Graphs Qinyong Wang Zhenxiang Gao Rong Xu AI4CE 23 5 0 25 Oct 2023
Projected Stochastic Gradient Descent with Quantum Annealed Binary Gradients Maximilian Krahn Michele Sasdelli Fengyi Yang Vladislav Golyanik Arno Solin Tat-Jun Chin Tolga Birdal MQ 87 2 0 23 Oct 2023
Marginal Nodes Matter: Towards Structure Fairness in Graphs Xiaotian Han Kaixiong Zhou Ting-Hsiang Wang Jundong Li Fei Wang Na Zou 34 0 0 23 Oct 2023
Graph Ranking Contrastive Learning: A Extremely Simple yet Efficient Method Yulan Hu Ouyang Sheng Jingyu Liu Ge Chen Zhirui Yang Junchen Wan Fuzheng Zhang Zhongyuan Wang Yong Liu 36 0 0 23 Oct 2023
Open-World Lifelong Graph Learning Marcel Hoffmann Lukas Galke A. Scherp 26 5 0 19 Oct 2023
Robust Graph Matching Using An Unbalanced Hierarchical Optimal Transport Framework Haoran Cheng Dixin Luo Hongteng Xu OT 23 0 0 18 Oct 2023
A Quasi-Wasserstein Loss for Learning Graph Neural Networks Minjie Cheng Hongteng Xu 30 1 0 18 Oct 2023
Fast Graph Condensation with Structure-based Neural Tangent Kernel Lin Wang Wenqi Fan Jiatong Li Yao Ma Qing Li DD 34 27 0 17 Oct 2023
LPFormer: An Adaptive Graph Transformer for Link Prediction Harry Shomer Yao Ma Haitao Mao Juanhui Li Bo Wu Jiliang Tang 38 7 0 17 Oct 2023
Node classification in networks via simplicial interactions Eunho Koo Tongseok Lim 33 0 0 16 Oct 2023
Does Graph Distillation See Like Vision Dataset Counterpart? Beining Yang Kai Wang Qingyun Sun Cheng Ji Xingcheng Fu Hao Tang Yang You Jianxin Li DD 22 39 0 13 Oct 2023
Infinite Width Graph Neural Networks for Node Regression/ Classification Yunus Cobanoglu AI4CE 26 1 0 12 Oct 2023
Non-backtracking Graph Neural Networks Seonghyun Park Narae Ryu Ga-Rin Kim Dongyeop Woo Se-Young Yun Sungsoo Ahn 35 4 0 11 Oct 2023
Are GATs Out of Balance? Nimrah Mustafa Aleksandar Bojchevski R. Burkholz 53 4 0 11 Oct 2023
Adversarial Robustness in Graph Neural Networks: A Hamiltonian Approach Kai Zhao Qiyu Kang Yang Song Rui She Sijie Wang Wee Peng Tay AAML 45 23 0 10 Oct 2023
Nonlinear Correct and Smooth for Semi-Supervised Learning Yuanhang Shao Xiuwen Liu 36 1 0 09 Oct 2023
GReAT: A Graph Regularized Adversarial Training Method Samet Bayram Kenneth Barner OOD AAML 30 1 0 09 Oct 2023
GSLB: The Graph Structure Learning Benchmark Zhixun Li Liang Wang Xin Sun Yifan Luo Yanqiao Zhu ... Xiangxin Zhou Qiang Liu Shu Wu Liang Wang Jeffrey Xu Yu 53 34 0 08 Oct 2023
Label-free Node Classification on Graphs with Large Language Models (LLMS) Zhikai Chen Haitao Mao Hongzhi Wen Haoyu Han Wei-dong Jin Haiyang Zhang Hui Liu Jiliang Tang 36 75 0 07 Oct 2023
Perfect Alignment May be Poisonous to Graph Contrastive Learning Jingyu Liu Huayi Tang Yong Liu 33 2 0 06 Oct 2023
GRAPES: Learning to Sample Graphs for Scalable Graph Neural Networks Taraneh Younesian Daniel Daza Emile van Krieken Thiviyan Thanapalasingam Peter Bloem 16 4 0 05 Oct 2023
DeepHGCN: Toward Deeper Hyperbolic Graph Convolutional Networks Jiaxu Liu Xinping Yi Xiaowei Huang 41 2 0 03 Oct 2023
Cooperative Graph Neural Networks Ben Finkelshtein Xingyue Huang Michael M. Bronstein .Ismail .Ilkan Ceylan GNN 47 20 0 02 Oct 2023