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CellCLAT: Preserving Topology and Trimming Redundancy in Self-Supervised Cellular Contrastive Learning

CellCLAT: Preserving Topology and Trimming Redundancy in Self-Supervised Cellular Contrastive Learning

27 May 2025
Bin Qin
Qirui Ji
Jiangmeng Li
Yupeng Wang
Xuesong Wu
Jianwen Cao
Fanjiang Xu
ArXivPDFHTML

Papers citing "CellCLAT: Preserving Topology and Trimming Redundancy in Self-Supervised Cellular Contrastive Learning"

14 / 14 papers shown
Title
TopoTune : A Framework for Generalized Combinatorial Complex Neural Networks
TopoTune : A Framework for Generalized Combinatorial Complex Neural Networks
Mathilde Papillon
Guillermo Bernardez
Claudio Battiloro
Nina Miolane
BDL
117
7
0
09 Oct 2024
CliquePH: Higher-Order Information for Graph Neural Networks through
  Persistent Homology on Clique Graphs
CliquePH: Higher-Order Information for Graph Neural Networks through Persistent Homology on Clique Graphs
Davide Buffelli
Farzin Soleymani
Bastian Rieck
GNN
45
1
0
12 Sep 2024
Topological Relational Learning on Graphs
Topological Relational Learning on Graphs
Yuzhou Chen
Baris Coskunuzer
Yulia R. Gel
59
43
0
29 Oct 2021
Graph Contrastive Learning Automated
Graph Contrastive Learning Automated
Yuning You
Tianlong Chen
Yang Shen
Zhangyang Wang
73
473
0
10 Jun 2021
Topological Graph Neural Networks
Topological Graph Neural Networks
Max Horn
E. Brouwer
Michael Moor
Yves Moreau
Bastian Rieck
Karsten Borgwardt
AI4CE
51
94
0
15 Feb 2021
TUDataset: A collection of benchmark datasets for learning with graphs
TUDataset: A collection of benchmark datasets for learning with graphs
Christopher Morris
Nils M. Kriege
Franka Bause
Kristian Kersting
Petra Mutzel
Marion Neumann
218
819
0
16 Jul 2020
Understanding Contrastive Representation Learning through Alignment and
  Uniformity on the Hypersphere
Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere
Tongzhou Wang
Phillip Isola
SSL
140
1,826
0
20 May 2020
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
143
861
0
31 Jul 2019
DARTS: Differentiable Architecture Search
DARTS: Differentiable Architecture Search
Hanxiao Liu
Karen Simonyan
Yiming Yang
185
4,345
0
24 Jun 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
170
3,450
0
05 May 2018
Neural Message Passing for Quantum Chemistry
Neural Message Passing for Quantum Chemistry
Justin Gilmer
S. Schoenholz
Patrick F. Riley
Oriol Vinyals
George E. Dahl
522
7,431
0
04 Apr 2017
Categorical Reparameterization with Gumbel-Softmax
Categorical Reparameterization with Gumbel-Softmax
Eric Jang
S. Gu
Ben Poole
BDL
291
5,360
0
03 Nov 2016
The Concrete Distribution: A Continuous Relaxation of Discrete Random
  Variables
The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables
Chris J. Maddison
A. Mnih
Yee Whye Teh
BDL
165
2,529
0
02 Nov 2016
node2vec: Scalable Feature Learning for Networks
node2vec: Scalable Feature Learning for Networks
Aditya Grover
J. Leskovec
183
10,856
0
03 Jul 2016
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