GraphSAINT: Graph Sampling Based Inductive Learning Method

10 July 2019

Papers citing "GraphSAINT: Graph Sampling Based Inductive Learning Method"

50 / 542 papers shown

Title
RAGFormer: Learning Semantic Attributes and Topological Structure for Fraud Detection Haolin Li Shuyang Jiang Lifeng Zhang Siyuan Du Guangnan Ye Hongfeng Chai 16 0 0 27 Feb 2024
Smoothed Graph Contrastive Learning via Seamless Proximity Integration M. Behmanesh M. Ovsjanikov 16 0 0 23 Feb 2024
AttackGNN: Red-Teaming GNNs in Hardware Security Using Reinforcement Learning Vasudev Gohil Satwik Patnaik D. Kalathil Jeyavijayan Rajendran AAML 25 3 0 21 Feb 2024
Scalable Graph Self-Supervised Learning Ali Saheb Pasand Reza Moravej Mahdi Biparva Raika Karimi Ali Ghodsi SSL 11 0 0 14 Feb 2024
Graph Inference Acceleration by Learning MLPs on Graphs without Supervision Zehong Wang Zheyuan Zhang Chuxu Zhang Yanfang Ye 14 0 0 14 Feb 2024
Rethinking Graph Masked Autoencoders through Alignment and Uniformity Liang Wang Xiang Tao Qiang Liu Shu Wu Liang Wang 23 13 0 11 Feb 2024
TASER: Temporal Adaptive Sampling for Fast and Accurate Dynamic Graph Representation Learning Gangda Deng Hongkuan Zhou Hanqing Zeng Yinglong Xia Christopher Leung Jianbo Li Rajgopal Kannan Viktor Prasanna 11 1 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
Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective Soo Yong Lee Sunwoo Kim Fanchen Bu Jaemin Yoo Jiliang Tang Kijung Shin 40 6 0 07 Feb 2024
On provable privacy vulnerabilities of graph representations Ruofan Wu Guanhua Fang Qiying Pan Mingyang Zhang Tengfei Liu Weiqiang Wang AAML 22 0 0 06 Feb 2024
ARGO: An Auto-Tuning Runtime System for Scalable GNN Training on Multi-Core Processor Yi-Chien Lin Yuyang Chen Sameh Gobriel Nilesh Jain Gopi Krishna Jha Viktor Prasanna GNN 22 3 0 06 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
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 44 25 0 03 Feb 2024
L2G2G: a Scalable Local-to-Global Network Embedding with Graph Autoencoders Ruikang Ouyang Andrew Elliott Stratis Limnios Mihai Cucuringu G. Reinert GNN 14 2 0 02 Feb 2024
Towards Effective and General Graph Unlearning via Mutual Evolution Xunkai Li Yulin Zhao Zhengyu Wu Wentao Zhang Ronghua Li Guoren Wang MU 20 13 0 22 Jan 2024
Disentangled Condensation for Large-scale Graphs Zhenbang Xiao Shunyu Liu Yu Wang Tongya Zheng Mingli Song Mingli Song Tongya Zheng DD 69 6 0 18 Jan 2024
GLISP: A Scalable GNN Learning System by Exploiting Inherent Structural Properties of Graphs Zhongshu Zhu Bin Jing Xiaopei Wan Zhizhen Liu Lei Liang Jun Zhou 14 2 0 06 Jan 2024
Graph Neural Networks for Tabular Data Learning: A Survey with Taxonomy and Directions Cheng-Te Li Yu-Che Tsai Chih-Yao Chen Jay Chiehen Liao LMTD AI4CE 25 7 0 04 Jan 2024
A clean-label graph backdoor attack method in node classification task Xiaogang Xing Ming Xu Yujing Bai Dongdong Yang AAML 76 7 0 30 Dec 2023
FALCON: Feature-Label Constrained Graph Net Collapse for Memory Efficient GNNs Christopher Adnel I. Rekik GNN 20 0 0 27 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
Robust Node Representation Learning via Graph Variational Diffusion Networks Jun Zhuang M. A. Hasan 8 7 0 18 Dec 2023
Neural Gaussian Similarity Modeling for Differential Graph Structure Learning Xiaolong Fan Maoguo Gong Yue Wu Zedong Tang Jie Liu 17 0 0 15 Dec 2023
MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training Hongwu Peng Xi Xie Kaustubh Shivdikar Md Amit Hasan Jiahui Zhao Shaoyi Huang Omer Khan David Kaeli Caiwen Ding 30 35 0 14 Dec 2023
GraphGuard: Detecting and Counteracting Training Data Misuse in Graph Neural Networks Bang Wu He Zhang Xiangwen Yang Shuo Wang Minhui Xue Shirui Pan Xingliang Yuan 45 6 0 13 Dec 2023
ASWT-SGNN: Adaptive Spectral Wavelet Transform-based Self-Supervised Graph Neural Network Ruyue Liu Rong Yin Yong Liu Weiping Wang SSL 13 3 0 10 Dec 2023
Isomorphic-Consistent Variational Graph Auto-Encoders for Multi-Level Graph Representation Learning Hanxuan Yang Qingchao Kong Wenji Mao BDL 8 0 0 09 Dec 2023
StructComp: Substituting Propagation with Structural Compression in Training Graph Contrastive Learning Shengzhong Zhang Wenjie Yang Xinyuan Cao Hongwei Zhang Zengfeng Huang 8 2 0 08 Dec 2023
Graph Neural Networks for Pressure Estimation in Water Distribution Systems Huy Truong Andres Tello Alexander Lazovik Victoria Degeler 18 7 0 17 Nov 2023
Distributed Constrained Combinatorial Optimization leveraging Hypergraph Neural Networks Nasimeh Heydaribeni Xinrui Zhan Ruisi Zhang Tina Eliassi-Rad F. Koushanfar AI4CE 27 8 0 15 Nov 2023
Classification of developmental and brain disorders via graph convolutional aggregation Ibrahim Salim A. B. Hamza MedIm 9 10 0 13 Nov 2023
GraNNDis: Efficient Unified Distributed Training Framework for Deep GNNs on Large Clusters Jaeyong Song Hongsun Jang Jaewon Jung Youngsok Kim Jinho Lee GNN 8 0 0 12 Nov 2023
Detecting Suspicious Commenter Mob Behaviors on YouTube Using Graph2Vec Shadi Shajari Mustafa Alassad Nitin Agarwal 13 2 0 09 Nov 2023
Distributed Matrix-Based Sampling for Graph Neural Network Training Alok Tripathy Katherine Yelick A. Buluç 16 3 0 06 Nov 2023
Entropy Aware Training for Fast and Accurate Distributed GNN Dhruv Deshmukh Gagan Raj Gupta Manisha Chawla Vishwesh Jatala Anirban Haldar 12 0 0 04 Nov 2023
Facilitating Graph Neural Networks with Random Walk on Simplicial Complexes Cai Zhou Xiyuan Wang Muhan Zhang 31 14 0 30 Oct 2023
Hyperbolic Graph Neural Networks at Scale: A Meta Learning Approach Nurendra Choudhary Nikhil S. Rao Chandan K. Reddy 14 5 0 29 Oct 2023
Graph Deep Learning for Time Series Forecasting Andrea Cini Ivan Marisca Daniele Zambon C. Alippi AI4TS AI4CE 19 14 0 24 Oct 2023
ABKD: Graph Neural Network Compression with Attention-Based Knowledge Distillation Anshul Ahluwalia Rohit Das Payman Behnam Alind Khare Pan Li Alexey Tumanov 14 2 0 24 Oct 2023
Efficient Heterogeneous Graph Learning via Random Projection Jun Hu Bryan Hooi Bingsheng He 28 9 0 23 Oct 2023
Cooperative Minibatching in Graph Neural Networks M. F. Balin Dominique LaSalle Ümit V. Çatalyürek GNN 20 1 0 19 Oct 2023
PREM: A Simple Yet Effective Approach for Node-Level Graph Anomaly Detection Junjun Pan Yixin Liu Yizhen Zheng Shirui Pan 27 18 0 18 Oct 2023
Fast Graph Condensation with Structure-based Neural Tangent Kernel Lin Wang Wenqi Fan Jiatong Li Yao Ma Qing Li DD 24 25 0 17 Oct 2023
Accelerating Scalable Graph Neural Network Inference with Node-Adaptive Propagation Xin Gao Wentao Zhang Junliang Yu Yingxiao Shao Quoc Viet Hung Nguyen Bin Cui Hongzhi Yin AI4CE GNN 22 9 0 17 Oct 2023
Graph Distillation with Eigenbasis Matching Yang Liu Deyu Bo Chuan Shi DD 26 9 0 13 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 11 38 0 13 Oct 2023
Global Minima, Recoverability Thresholds, and Higher-Order Structure in GNNS Drake Brown Trevor Garrity Kaden Parker Jason Oliphant Stone Carson Cole Hanson Zachary Boyd 14 0 0 11 Oct 2023
Data-centric Graph Learning: A Survey Jixi Liu Deyu Bo Cheng Yang Haoran Dai Qi Zhang Yixin Xiao Yufei Peng Chuan Shi GNN 16 19 0 08 Oct 2023
GRAPES: Learning to Sample Graphs for Scalable Graph Neural Networks Taraneh Younesian Daniel Daza Emile van Krieken Thiviyan Thanapalasingam Peter Bloem 14 4 0 05 Oct 2023