FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling

30 January 2018

Papers citing "FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling"

50 / 694 papers shown

Title
Do We Really Need Graph Neural Networks for Traffic Forecasting? Xu Liu Keli Zhang Chao Huang Hengchang Hu Yushi Cao Bryan Hooi Roger Zimmermann AI4TS 24 20 0 30 Jan 2023
Simplifying Subgraph Representation Learning for Scalable Link Prediction Paul Louis Shweta Ann Jacob Amirali Salehi-Abari 18 8 0 29 Jan 2023
Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure Ryoma Sato 37 5 0 26 Jan 2023
Understanding and Improving Deep Graph Neural Networks: A Probabilistic Graphical Model Perspective Jiayuan Chen Xiang Zhang Yinfei Xu Tianli Zhao Renjie Xie Wei Xu GNN BDL 23 0 0 25 Jan 2023
GIPA: A General Information Propagation Algorithm for Graph Learning Houyi Li Zhihong Chen Zhao Li Qinkai Zheng Peng Zhang Shuigeng Zhou 49 0 0 19 Jan 2023
FreshGNN: Reducing Memory Access via Stable Historical Embeddings for Graph Neural Network Training Kezhao Huang Haitian Jiang Minjie Wang Guangxuan Xiao David Wipf Xiang Song Quan Gan Zengfeng Huang Jidong Zhai Zheng-Wei Zhang GNN 33 2 0 18 Jan 2023
A Network Science perspective of Graph Convolutional Networks: A survey Mingshan Jia Bogdan Gabrys Katarzyna Musial GNN 32 7 0 12 Jan 2023
Predicting Hateful Discussions on Reddit using Graph Transformer Networks and Communal Context Liam Hebert Lukasz Golab R. Cohen 11 8 0 10 Jan 2023
GUAP: Graph Universal Attack Through Adversarial Patching Xiao Zang Jie Chen Bo Yuan AAML 17 4 0 04 Jan 2023
Adversarial Virtual Exemplar Learning for Label-Frugal Satellite Image Change Detection H. Sahbi Sebastien Deschamps 23 0 0 28 Dec 2022
Training Lightweight Graph Convolutional Networks with Phase-field Models H. Sahbi 29 0 0 19 Dec 2022
Influence-Based Mini-Batching for Graph Neural Networks Johannes Gasteiger Chao Qian Stephan Günnemann GNN 32 13 0 18 Dec 2022
Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs Chenxiao Yang Qitian Wu Jiahua Wang Junchi Yan AI4CE 19 51 0 18 Dec 2022
Graph Learning and Its Advancements on Large Language Models: A Holistic Survey Shaopeng Wei Yu Zhao Xingyan Chen Qing Li Fuzhen Zhuang Ji Liu Fuji Ren Gang Kou AI4CE 27 5 0 17 Dec 2022
Scalable Graph Convolutional Network Training on Distributed-Memory Systems G. Demirci Aparajita Haldar Hakan Ferhatosmanoglu GNN 36 9 0 09 Dec 2022
Frugal Reinforcement-based Active Learning Sebastien Deschamps H. Sahbi 16 0 0 09 Dec 2022
DGI: Easy and Efficient Inference for GNNs Peiqi Yin Xiao Yan Jinjing Zhou Qiang Fu Zhenkun Cai James Cheng Bo Tang Minjie Wang GNN 30 4 0 28 Nov 2022
GREAD: Graph Neural Reaction-Diffusion Networks Jeongwhan Choi Seoyoung Hong Noseong Park Sung-Bae Cho DiffM GNN 21 27 0 25 Nov 2022
From Node Interaction to Hop Interaction: New Effective and Scalable Graph Learning Paradigm Jie Chen Zilong Li Ying Zhu Junping Zhang Jian Pu 36 8 0 21 Nov 2022
Unifying Label-inputted Graph Neural Networks with Deep Equilibrium Models Yi Luo Guiduo Duan Guangchun Luo Aiguo Chen 23 1 0 19 Nov 2022
Hierarchical Estimation for Effective and Efficient Sampling Graph Neural Network Heng Chang Bingbing Xu Qi Cao Yige Yuan Huawei Shen 21 0 0 16 Nov 2022
A Comprehensive Survey on Distributed Training of Graph Neural Networks Haiyang Lin Yurui Lai Xiaochun Ye Xiaochun Ye Shirui Pan Wenguang Chen Yuan Xie GNN 30 24 0 10 Nov 2022
Characterizing the Efficiency of Graph Neural Network Frameworks with a Magnifying Glass Xin Huang Jongryool Kim Brad Rees Chul-Ho Lee GNN 29 4 0 06 Nov 2022
Efficient Graph Neural Network Inference at Large Scale Xin-pu Gao Wentao Zhang Yingxia Shao Quoc Viet Hung Nguyen Bin Cui Hongzhi Yin AI4CE GNN 52 9 0 01 Nov 2022
Distributed Graph Neural Network Training: A Survey Yingxia Shao Hongzheng Li Xizhi Gu Hongbo Yin Yawen Li Xupeng Miao Wentao Zhang Bin Cui Lei Chen GNN AI4CE 11 56 0 01 Nov 2022
Towards Relation-centered Pooling and Convolution for Heterogeneous Graph Learning Networks Tiehua Zhang Yuze Liu Yaohan Yao Youhua Xia Xin Chen Xiaowei Huang Jiongdao Jin 26 2 0 31 Oct 2022
Layer-Neighbor Sampling -- Defusing Neighborhood Explosion in GNNs M. F. Balin Ümit V. Çatalyürek 27 15 0 24 Oct 2022
Binary Graph Convolutional Network with Capacity Exploration Junfu Wang Yuanfang Guo Liang Yang Yun-an Wang GNN 30 5 0 24 Oct 2022
gSuite: A Flexible and Framework Independent Benchmark Suite for Graph Neural Network Inference on GPUs Taha Tekdogan Serkan Göktas Ayse Yilmazer-Metin 28 0 0 20 Oct 2022
SA-MLP: Distilling Graph Knowledge from GNNs into Structure-Aware MLP Jie Chen Shouzhen Chen Mingyuan Bai Junbin Gao Junping Zhang Jian Pu 40 10 0 18 Oct 2022
Learning to Sample and Aggregate: Few-shot Reasoning over Temporal Knowledge Graphs Ruijie Wang Zheng Li Dachun Sun Shengzhong Liu Jinning Li Bing Yin Tarek F. Abdelzaher OffRL 21 41 0 16 Oct 2022
Old can be Gold: Better Gradient Flow can Make Vanilla-GCNs Great Again Ajay Jaiswal Peihao Wang Tianlong Chen Justin F. Rousseau Ying Ding Zhangyang Wang 35 10 0 14 Oct 2022
A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking Keyu Duan Zirui Liu Peihao Wang Wenqing Zheng Kaixiong Zhou Tianlong Chen Xia Hu Zhangyang Wang GNN 41 57 0 14 Oct 2022
Characterizing the Influence of Graph Elements Zizhang Chen Peizhao Li Hongfu Liu Pengyu Hong TDI 21 20 0 14 Oct 2022
JuryGCN: Quantifying Jackknife Uncertainty on Graph Convolutional Networks Jian Kang Qinghai Zhou Hanghang Tong UQCV 41 21 0 12 Oct 2022
Generalized energy and gradient flow via graph framelets Andi Han Dai Shi Zhiqi Shao Junbin Gao 75 13 0 08 Oct 2022
Towards Real-Time Temporal Graph Learning Deniz Gurevin Mohsin Shan Tong Geng Weiwen Jiang Caiwen Ding O. Khan AI4TS AI4CE 43 0 0 08 Oct 2022
Robust Graph Structure Learning via Multiple Statistical Tests Yaohua Wang Fangyi Zhang Ming Lin Senzhang Wang Xiuyu Sun Rong Jin 34 1 0 08 Oct 2022
Hierarchical Graph Transformer with Adaptive Node Sampling Zaixin Zhang Qi Liu Qingyong Hu Cheekong Lee 78 82 0 08 Oct 2022
Uncovering the Structural Fairness in Graph Contrastive Learning Ruijia Wang Xiao Wang Chuan Shi Le Song 95 31 0 06 Oct 2022
Teaching Yourself: Graph Self-Distillation on Neighborhood for Node Classification Lirong Wu Jun Xia Haitao Lin Zhangyang Gao Zicheng Liu Guojiang Zhao Stan Z. Li 61 6 0 05 Oct 2022
Towards Prototype-Based Self-Explainable Graph Neural Network Enyan Dai Suhang Wang 33 12 0 05 Oct 2022
Federated Graph-based Networks with Shared Embedding Tianyi Yu Pei-Ci Lai Fei Teng FedML 34 3 0 03 Oct 2022
Diving into Unified Data-Model Sparsity for Class-Imbalanced Graph Representation Learning Chunhui Zhang Chao Huang Yijun Tian Qianlong Wen Z. Ouyang Youhuan Li Yanfang Ye Chuxu Zhang 25 6 0 01 Oct 2022
GPNet: Simplifying Graph Neural Networks via Multi-channel Geometric Polynomials Xun Liu Alex Hay-Man Ng Fangyu Lei Yikuan Zhang Zhengmin Li GNN 22 2 0 30 Sep 2022
Flattened Graph Convolutional Networks For Recommendation Yue Xu Hao Chen Zengde Deng Yuan-Qi Bei Feiran Huang BDL GNN 21 1 0 25 Sep 2022
Enabling Homogeneous GNNs to Handle Heterogeneous Graphs via Relation Embedding Junfu Wang Yuanfang Guo Liang Yang Yun-an Wang 32 8 0 23 Sep 2022
Hub-aware Random Walk Graph Embedding Methods for Classification Aleksandar Tomcic Miloš Savić Miloš Radovanović 16 2 0 15 Sep 2022
A semantic hierarchical graph neural network for text classification Shuai Hua Xinxin Li Yun Jing Qu Liu 17 3 0 15 Sep 2022
MGG: Accelerating Graph Neural Networks with Fine-grained intra-kernel Communication-Computation Pipelining on Multi-GPU Platforms Yuke Wang Boyuan Feng Zheng Wang Tong Geng Kevin J. Barker Ang Li Yufei Ding GNN 45 25 0 14 Sep 2022