G-Mixup: Graph Data Augmentation for Graph Classification

15 February 2022

Ninghao Liu

Papers citing "G-Mixup: Graph Data Augmentation for Graph Classification"

26 / 26 papers shown

Title
CAMeL: Cross-modality Adaptive Meta-Learning for Text-based Person Retrieval Hang Yu Jiahao Wen Zhedong Zheng 46 0 0 26 Apr 2025
Diffusion on Graph: Augmentation of Graph Structure for Node Classification Yancheng Wang Changyu Liu Yingzhen Yang DiffM GNN 71 0 0 16 Mar 2025
Towards Pattern-aware Data Augmentation for Temporal Knowledge Graph Completion Jiasheng Zhang Deqiang Ouyang Shuang Liang Jie Shao 25 0 0 03 Jan 2025
A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation Kexin Zhang Shuhan Liu Song Wang Weili Shi Chen Chen Pan Li Sheng R. Li Jundong Li Kaize Ding OOD 45 2 0 25 Oct 2024
MALADY: Multiclass Active Learning with Auction Dynamics on Graphs Gokul Bhusal Kevin Miller E. Merkurjev 30 0 0 14 Sep 2024
Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization Wenyu Mao Jiancan Wu Haoyang Liu Yongduo Sui Xiang Wang OOD 37 2 0 03 Aug 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 19 0 15 May 2024
Through the Dual-Prism: A Spectral Perspective on Graph Data Augmentation for Graph Classification Yutong Xia Runpeng Yu Yuxuan Liang Xavier Bresson Xinchao Wang Roger Zimmermann 35 4 0 18 Jan 2024
Graph Invariant Learning with Subgraph Co-mixup for Out-Of-Distribution Generalization Tianrui Jia Haoyang Li Cheng Yang Tao Tao Chuan Shi OOD 15 17 0 18 Dec 2023
Exploring Graph Classification Techniques Under Low Data Constraints: A Comprehensive Study Kush Kothari Bhavya Mehta Reshmika Nambiar S. Shrawne 13 0 0 21 Nov 2023
Better with Less: A Data-Active Perspective on Pre-Training Graph Neural Networks Jiarong Xu Renhong Huang Xin Jiang Yuxuan Cao Carl Yang Chunping Wang Yang Yang AI4CE 25 14 0 02 Nov 2023
R-Mixup: Riemannian Mixup for Biological Networks Xuan Kan Zimu Li Hejie Cui Yue Yu Ran Xu Shaojun Yu Zilong Zhang Ying Guo Carl Yang 22 6 0 05 Jun 2023
Editable Graph Neural Network for Node Classifications Zirui Liu Zhimeng Jiang Shaochen Zhong Kaixiong Zhou Li Li Rui Chen Soo-Hyun Choi Xia Hu 13 6 0 24 May 2023
Boosting long-term forecasting performance for continuous-time dynamic graph networks via data augmentation Yu Tian Mingjie Zhu Jiachi Luo Song Li 16 0 0 12 Apr 2023
Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling Haotao Wang Ziyu Jiang Yuning You Yan Han Gaowen Liu Jayanth Srinivasa Ramana Rao Kompella Zhangyang Wang 16 27 0 06 Apr 2023
A Generalization of ViT/MLP-Mixer to Graphs Xiaoxin He Bryan Hooi T. Laurent Adam Perold Yann LeCun Xavier Bresson 22 88 0 27 Dec 2022
Data Augmentation on Graphs: A Technical Survey Jiajun Zhou Chenxuan Xie Shengbo Gong Z. Wen Xiangyu Zhao Qi Xuan Xiaoniu Yang AI4TS 14 8 0 20 Dec 2022
GraphMAD: Graph Mixup for Data Augmentation using Data-Driven Convex Clustering Madeline Navarro Santiago Segarra 30 7 0 27 Oct 2022
RSC: Accelerating Graph Neural Networks Training via Randomized Sparse Computations Zirui Liu Sheng-Wei Chen Kaixiong Zhou Daochen Zha Xiao Huang Xia Hu 24 14 0 19 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 24 10 0 18 Oct 2022
GraphTTA: Test Time Adaptation on Graph Neural Networks Guan-Wun Chen Jiying Zhang Xi Xiao Y. Li OOD 25 9 0 19 Aug 2022
Metric Based Few-Shot Graph Classification Donato Crisostomi Simone Antonelli Valentino Maiorca Luca Moschella R. Marin Emanuele Rodolà 13 5 0 08 Jun 2022
Graph Data Augmentation for Graph Machine Learning: A Survey Tong Zhao Wei Jin Yozen Liu Yingheng Wang Gang Liu Stephan Günnemann Neil Shah Meng-Long Jiang OOD 17 78 0 17 Feb 2022
Graph Transplant: Node Saliency-Guided Graph Mixup with Local Structure Preservation Joonhyung Park Hajin Shim Eunho Yang 79 49 0 10 Nov 2021
Calibrating and Improving Graph Contrastive Learning Kaili Ma Haochen Yang Han Yang Yongqiang Chen James Cheng 30 6 0 27 Jan 2021
Learning Graphons via Structured Gromov-Wasserstein Barycenters Hongteng Xu Dixin Luo Lawrence Carin H. Zha 41 28 0 10 Dec 2020