Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling

6 April 2023

Papers citing "Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling"

35 / 35 papers shown

Title
Nonparametric Teaching for Graph Property Learners Chen Zhang Weixin Bu Zhaochun Ren Ziyue Liu Yik-Chung Wu Ngai Wong 89 0 0 20 May 2025
Mix-of-Granularity: Optimize the Chunking Granularity for Retrieval-Augmented Generation Zijie Zhong Hanwen Liu Xiaoya Cui Xiaofan Zhang Zengchang Qin 120 8 0 28 Jan 2025
One Model for One Graph: A New Perspective for Pretraining with Cross-domain Graphs J. Liu Haitao Mao Zhikai Chen Wenqi Fan Mingxuan Ju Tong Zhao Neil Shah Neil Shah Jiliang Tang AI4CE 185 3 0 30 Nov 2024
GETS: Ensemble Temperature Scaling for Calibration in Graph Neural Networks Dingyi Zhuang Chonghe Jiang Yunhan Zheng Shenhao Wang Jinhua Zhao UQCV 86 0 0 12 Oct 2024
M $^3$ ViT: Mixture-of-Experts Vision Transformer for Efficient Multi-task Learning with Model-Accelerator Co-design Hanxue Liang Zhiwen Fan Rishov Sarkar Ziyu Jiang Tianlong Chen Kai Zou Yu Cheng Cong Hao Zhangyang Wang MoE 62 86 0 26 Oct 2022
Context-aware Mixture-of-Experts for Unbiased Scene Graph Generation Liguang Zhou Yuhongze Zhou Tin Lun Lam Yangsheng Xu EDL MoE 45 2 0 15 Aug 2022
Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts Basil Mustafa C. Riquelme J. Puigcerver Rodolphe Jenatton N. Houlsby VLM MoE 130 194 0 06 Jun 2022
Training Compute-Optimal Large Language Models Jordan Hoffmann Sebastian Borgeaud A. Mensch Elena Buchatskaya Trevor Cai ... Karen Simonyan Erich Elsen Jack W. Rae Oriol Vinyals Laurent Sifre AI4TS 167 1,936 0 29 Mar 2022
G-Mixup: Graph Data Augmentation for Graph Classification Xiaotian Han Zhimeng Jiang Ninghao Liu Xia Hu 62 199 0 15 Feb 2022
Local Augmentation for Graph Neural Networks Songtao Liu Rex Ying Hanze Dong Lanqing Li Tingyang Xu Yu Rong P. Zhao Junzhou Huang Dinghao Wu 82 93 0 08 Sep 2021
Pooling Architecture Search for Graph Classification Lan Wei Huan Zhao Quanming Yao Zhiqiang He AI4CE 41 73 0 24 Aug 2021
From Canonical Correlation Analysis to Self-supervised Graph Neural Networks Hengrui Zhang Qitian Wu Junchi Yan David Wipf Philip S. Yu SSL 50 219 0 23 Jun 2021
Scaling Vision with Sparse Mixture of Experts C. Riquelme J. Puigcerver Basil Mustafa Maxim Neumann Rodolphe Jenatton André Susano Pinto Daniel Keysers N. Houlsby MoE 74 597 0 10 Jun 2021
Graph Contrastive Learning Automated Yuning You Tianlong Chen Yang Shen Zhangyang Wang 73 472 0 10 Jun 2021
Hash Layers For Large Sparse Models Stephen Roller Sainbayar Sukhbaatar Arthur Szlam Jason Weston MoE 152 210 0 08 Jun 2021
BASE Layers: Simplifying Training of Large, Sparse Models M. Lewis Shruti Bhosale Tim Dettmers Naman Goyal Luke Zettlemoyer MoE 165 277 0 30 Mar 2021
High-Performance Large-Scale Image Recognition Without Normalization Andrew Brock Soham De Samuel L. Smith Karen Simonyan VLM 259 517 0 11 Feb 2021
Graph Neural Network for Traffic Forecasting: A Survey Weiwei Jiang Jiayun Luo GNN AI4TS AI4CE 176 866 0 27 Jan 2021
Large-scale Robust Deep AUC Maximization: A New Surrogate Loss and Empirical Studies on Medical Image Classification Zhuoning Yuan Yan Yan Milan Sonka Tianbao Yang AI4TS MedIm OOD 58 120 0 06 Dec 2020
Graph Neural Networks in Recommender Systems: A Survey Shiwen Wu Fei Sun Wentao Zhang Xu Xie Tengjiao Wang GNN 121 1,218 0 04 Nov 2020
Graph Contrastive Learning with Adaptive Augmentation Yanqiao Zhu Yichen Xu Feng Yu Qiang Liu Shu Wu Liang Wang 75 1,103 0 27 Oct 2020
GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding Dmitry Lepikhin HyoukJoong Lee Yuanzhong Xu Dehao Chen Orhan Firat Yanping Huang M. Krikun Noam M. Shazeer Zhiwen Chen MoE 82 1,156 0 30 Jun 2020
DeeperGCN: All You Need to Train Deeper GCNs Guohao Li Chenxin Xiong Ali K. Thabet Guohao Li GNN 154 440 0 13 Jun 2020
Open Graph Benchmark: Datasets for Machine Learning on Graphs Weihua Hu Matthias Fey Marinka Zitnik Yuxiao Dong Hongyu Ren Bowen Liu Michele Catasta J. Leskovec 269 2,719 0 02 May 2020
Adversarial Examples Improve Image Recognition Cihang Xie Mingxing Tan Boqing Gong Jiang Wang Alan Yuille Quoc V. Le AAML 114 565 0 21 Nov 2019
Symmetric Graph Convolutional Autoencoder for Unsupervised Graph Representation Learning Jiwoong Park Minsik Lee H. Chang Kyuewang Lee J. Choi SSL 76 236 0 07 Aug 2019
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization Fan-Yun Sun Jordan Hoffmann Vikas Verma Jian Tang SSL 143 861 0 31 Jul 2019
Strategies for Pre-training Graph Neural Networks Weihua Hu Bowen Liu Joseph Gomes Marinka Zitnik Percy Liang Vijay S. Pande J. Leskovec SSL AI4CE 96 1,398 0 29 May 2019
Graph Attention Auto-Encoders Amin Salehi H. Davulcu GNN 49 120 0 26 May 2019
How Powerful are Graph Neural Networks? Keyulu Xu Weihua Hu J. Leskovec Stefanie Jegelka GNN 208 7,623 0 01 Oct 2018
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation Jiaxuan You Bowen Liu Rex Ying Vijay S. Pande J. Leskovec GNN 274 902 0 07 Jun 2018
N-GCN: Multi-scale Graph Convolution for Semi-supervised Node Classification Sami Abu-El-Haija Amol Kapoor Bryan Perozzi Joonseok Lee GNN SSL 63 260 0 24 Feb 2018
Graph Attention Networks Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Lio Yoshua Bengio GNN 413 20,061 0 30 Oct 2017
Inductive Representation Learning on Large Graphs William L. Hamilton Z. Ying J. Leskovec 442 15,179 0 07 Jun 2017
Neural Message Passing for Quantum Chemistry Justin Gilmer S. Schoenholz Patrick F. Riley Oriol Vinyals George E. Dahl 413 7,431 0 04 Apr 2017