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Bringing Your Own View: Graph Contrastive Learning without Prefabricated
  Data Augmentations

Bringing Your Own View: Graph Contrastive Learning without Prefabricated Data Augmentations

4 January 2022
Yuning You
Tianlong Chen
Zhangyang Wang
Yang Shen
    SSL
ArXivPDFHTML

Papers citing "Bringing Your Own View: Graph Contrastive Learning without Prefabricated Data Augmentations"

16 / 16 papers shown
Title
Heterogeneous Contrastive Learning for Foundation Models and Beyond
Heterogeneous Contrastive Learning for Foundation Models and Beyond
Lecheng Zheng
Baoyu Jing
Zihao Li
Hanghang Tong
Jingrui He
VLM
24
19
0
30 Mar 2024
Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit
  Diversity Modeling
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
Neural Algorithmic Reasoning with Causal Regularisation
Neural Algorithmic Reasoning with Causal Regularisation
Beatrice Bevilacqua
Kyriacos Nikiforou
Borja Ibarz
Ioana Bica
Michela Paganini
Charles Blundell
Jovana Mitrović
Petar Velivcković
OOD
CML
NAI
24
26
0
20 Feb 2023
Spectral Feature Augmentation for Graph Contrastive Learning and Beyond
Spectral Feature Augmentation for Graph Contrastive Learning and Beyond
Yifei Zhang
Hao Zhu
Zixing Song
Piotr Koniusz
Irwin King
19
87
0
02 Dec 2022
Augmentations in Hypergraph Contrastive Learning: Fabricated and
  Generative
Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative
Tianxin Wei
Yuning You
Tianlong Chen
Yang Shen
Jingrui He
Zhangyang Wang
16
45
0
07 Oct 2022
Graph Contrastive Learning with Personalized Augmentation
Graph Contrastive Learning with Personalized Augmentation
X. Zhang
Qiaoyu Tan
Xiao Shi Huang
Bo-wen Li
28
15
0
14 Sep 2022
A Survey of Pretraining on Graphs: Taxonomy, Methods, and Applications
A Survey of Pretraining on Graphs: Taxonomy, Methods, and Applications
Jun-Xiong Xia
Yanqiao Zhu
Yuanqi Du
Stan Z. Li
VLM
30
41
0
16 Feb 2022
ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning
ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning
Jun-Xiong Xia
Lirong Wu
Ge Wang
Jintao Chen
Stan Z. Li
25
120
0
05 Oct 2021
Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive
  Benchmark Study
Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study
Tianlong Chen
Kaixiong Zhou
Keyu Duan
Wenqing Zheng
Peihao Wang
Xia Hu
Zhangyang Wang
AAML
GNN
19
61
0
24 Aug 2021
Node Embedding using Mutual Information and Self-Supervision based
  Bi-level Aggregation
Node Embedding using Mutual Information and Self-Supervision based Bi-level Aggregation
Kashob Kumar Roy
Amit Roy
A. Rahman
M. A. Amin
A. Ali
SSL
16
10
0
27 Apr 2021
GraphDF: A Discrete Flow Model for Molecular Graph Generation
GraphDF: A Discrete Flow Model for Molecular Graph Generation
Youzhi Luo
Keqiang Yan
Shuiwang Ji
DRL
168
187
0
01 Feb 2021
Graph Information Bottleneck
Graph Information Bottleneck
Tailin Wu
Hongyu Ren
Pan Li
J. Leskovec
AAML
88
224
0
24 Oct 2020
Iterative Graph Self-Distillation
Iterative Graph Self-Distillation
Hanlin Zhang
Shuai Lin
Weiyang Liu
Pan Zhou
Jian Tang
Xiaodan Liang
Eric P. Xing
SSL
42
33
0
23 Oct 2020
L$^2$-GCN: Layer-Wise and Learned Efficient Training of Graph
  Convolutional Networks
L2^22-GCN: Layer-Wise and Learned Efficient Training of Graph Convolutional Networks
Yuning You
Tianlong Chen
Zhangyang Wang
Yang Shen
GNN
86
82
0
30 Mar 2020
Junction Tree Variational Autoencoder for Molecular Graph Generation
Junction Tree Variational Autoencoder for Molecular Graph Generation
Wengong Jin
Regina Barzilay
Tommi Jaakkola
219
1,332
0
12 Feb 2018
MoleculeNet: A Benchmark for Molecular Machine Learning
MoleculeNet: A Benchmark for Molecular Machine Learning
Zhenqin Wu
Bharath Ramsundar
Evan N. Feinberg
Joseph Gomes
C. Geniesse
Aneesh S. Pappu
K. Leswing
Vijay S. Pande
OOD
159
1,766
0
02 Mar 2017
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