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Uncovering Capabilities of Model Pruning in Graph Contrastive Learning

Uncovering Capabilities of Model Pruning in Graph Contrastive Learning

27 October 2024
Wu Junran
Chen Xueyuan
Li Shangzhe
ArXiv (abs)PDFHTML

Papers citing "Uncovering Capabilities of Model Pruning in Graph Contrastive Learning"

26 / 26 papers shown
Title
Do LLMs Understand Visual Anomalies? Uncovering LLM's Capabilities in Zero-shot Anomaly Detection
Do LLMs Understand Visual Anomalies? Uncovering LLM's Capabilities in Zero-shot Anomaly Detection
Jiaqi Zhu
Shaofeng Cai
Fang Deng
Junran Wu
Junran Wu
110
16
0
15 Apr 2024
HILL: Hierarchy-aware Information Lossless Contrastive Learning for
  Hierarchical Text Classification
HILL: Hierarchy-aware Information Lossless Contrastive Learning for Hierarchical Text Classification
He Zhu
Junran Wu
Ruomei Liu
Yue Hou
Ze Yuan
Shangzhe Li
Yicheng Pan
Ke Xu
31
6
0
26 Mar 2024
A Simple yet Effective Method for Graph Classification
A Simple yet Effective Method for Graph Classification
Junran Wu
Shangzhe Li
Jianhao Li
Yicheng Pan
Keyulu Xu
123
26
0
06 Jun 2022
Adversarial Graph Contrastive Learning with Information Regularization
Adversarial Graph Contrastive Learning with Information Regularization
Shengyu Feng
Baoyu Jing
Yada Zhu
Hanghang Tong
50
66
0
14 Feb 2022
Graph Self-supervised Learning with Accurate Discrepancy Learning
Graph Self-supervised Learning with Accurate Discrepancy Learning
Dongki Kim
Jinheon Baek
Sung Ju Hwang
SSL
52
38
0
07 Feb 2022
Molecular Contrastive Learning with Chemical Element Knowledge Graph
Molecular Contrastive Learning with Chemical Element Knowledge Graph
Yin Fang
Qiang Zhang
Haihong Yang
Xiang Zhuang
Shumin Deng
Wen Zhang
Minghai Qin
Zhuo Chen
Xiaohui Fan
Huajun Chen
62
111
0
01 Dec 2021
AutoGCL: Automated Graph Contrastive Learning via Learnable View
  Generators
AutoGCL: Automated Graph Contrastive Learning via Learnable View Generators
Yihang Yin
Qingzhong Wang
Siyu Huang
Haoyi Xiong
Xiang Zhang
89
150
0
21 Sep 2021
Graph Contrastive Learning Automated
Graph Contrastive Learning Automated
Yuning You
Tianlong Chen
Yang Shen
Zhangyang Wang
81
476
0
10 Jun 2021
Can Subnetwork Structure be the Key to Out-of-Distribution
  Generalization?
Can Subnetwork Structure be the Key to Out-of-Distribution Generalization?
Dinghuai Zhang
Kartik Ahuja
Yilun Xu
Yisen Wang
Aaron Courville
OOD
84
96
0
05 Jun 2021
Contrastive Multi-View Representation Learning on Graphs
Contrastive Multi-View Representation Learning on Graphs
Kaveh Hassani
Amir Hosein Khas Ahmadi
SSL
230
1,302
0
10 Jun 2020
A Simple Framework for Contrastive Learning of Visual Representations
A Simple Framework for Contrastive Learning of Visual Representations
Ting-Li Chen
Simon Kornblith
Mohammad Norouzi
Geoffrey E. Hinton
SSL
369
18,778
0
13 Feb 2020
Proving the Lottery Ticket Hypothesis: Pruning is All You Need
Proving the Lottery Ticket Hypothesis: Pruning is All You Need
Eran Malach
Gilad Yehudai
Shai Shalev-Shwartz
Ohad Shamir
104
275
0
03 Feb 2020
Momentum Contrast for Unsupervised Visual Representation Learning
Momentum Contrast for Unsupervised Visual Representation Learning
Kaiming He
Haoqi Fan
Yuxin Wu
Saining Xie
Ross B. Girshick
SSL
204
12,085
0
13 Nov 2019
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation
  Learning via Mutual Information Maximization
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization
Fan-Yun Sun
Jordan Hoffmann
Vikas Verma
Jian Tang
SSL
153
862
0
31 Jul 2019
XLNet: Generalized Autoregressive Pretraining for Language Understanding
XLNet: Generalized Autoregressive Pretraining for Language Understanding
Zhilin Yang
Zihang Dai
Yiming Yang
J. Carbonell
Ruslan Salakhutdinov
Quoc V. Le
AI4CE
232
8,433
0
19 Jun 2019
Strategies for Pre-training Graph Neural Networks
Strategies for Pre-training Graph Neural Networks
Weihua Hu
Bowen Liu
Joseph Gomes
Marinka Zitnik
Percy Liang
Vijay S. Pande
J. Leskovec
SSLAI4CE
116
1,404
0
29 May 2019
How Powerful are Graph Neural Networks?
How Powerful are Graph Neural Networks?
Keyulu Xu
Weihua Hu
J. Leskovec
Stefanie Jegelka
GNN
243
7,653
0
01 Oct 2018
Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks
Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks
Yang He
Guoliang Kang
Xuanyi Dong
Yanwei Fu
Yi Yang
AAMLVLM
66
964
0
21 Aug 2018
Unsupervised Feature Learning via Non-Parametric Instance-level
  Discrimination
Unsupervised Feature Learning via Non-Parametric Instance-level Discrimination
Zhirong Wu
Yuanjun Xiong
Stella X. Yu
Dahua Lin
SSL
179
3,458
0
05 May 2018
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
Jonathan Frankle
Michael Carbin
240
3,473
0
09 Mar 2018
graph2vec: Learning Distributed Representations of Graphs
graph2vec: Learning Distributed Representations of Graphs
A. Narayanan
Mahinthan Chandramohan
R. Venkatesan
Lihui Chen
Yang Liu
Shantanu Jaiswal
GNN
71
742
0
17 Jul 2017
Neural Message Passing for Quantum Chemistry
Neural Message Passing for Quantum Chemistry
Justin Gilmer
S. Schoenholz
Patrick F. Riley
Oriol Vinyals
George E. Dahl
593
7,455
0
04 Apr 2017
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
337
1,827
0
02 Mar 2017
Pruning Filters for Efficient ConvNets
Pruning Filters for Efficient ConvNets
Hao Li
Asim Kadav
Igor Durdanovic
H. Samet
H. Graf
3DPC
193
3,697
0
31 Aug 2016
node2vec: Scalable Feature Learning for Networks
node2vec: Scalable Feature Learning for Networks
Aditya Grover
J. Leskovec
191
10,876
0
03 Jul 2016
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.9K
150,115
0
22 Dec 2014
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