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A Probabilistic Graph Coupling View of Dimension Reduction

A Probabilistic Graph Coupling View of Dimension Reduction

31 January 2022
Hugues van Assel
T. Espinasse
J. Chiquet
F. Picard
ArXivPDFHTML

Papers citing "A Probabilistic Graph Coupling View of Dimension Reduction"

11 / 11 papers shown
Title
Dimension Reduction with Locally Adjusted Graphs
Dimension Reduction with Locally Adjusted Graphs
Yingfan Wang
Yiyang Sun
Haiyang Huang
Cynthia Rudin
80
1
0
19 Dec 2024
Assessing and improving reliability of neighbor embedding methods: a map-continuity perspective
Assessing and improving reliability of neighbor embedding methods: a map-continuity perspective
Zhexuan Liu
Rong Ma
Yiqiao Zhong
62
0
0
22 Oct 2024
Towards One Model for Classical Dimensionality Reduction: A Probabilistic Perspective on UMAP and t-SNE
Towards One Model for Classical Dimensionality Reduction: A Probabilistic Perspective on UMAP and t-SNE
Aditya Ravuri
Neil D. Lawrence
28
1
0
27 May 2024
Entity Alignment with Unlabeled Dangling Cases
Entity Alignment with Unlabeled Dangling Cases
Hang Yin
Dong Ding
Liyao Xiang
Yuheng He
Yihan Wu
Xinbing Wang
Cheng Zhou
25
0
0
16 Mar 2024
Distributional Reduction: Unifying Dimensionality Reduction and
  Clustering with Gromov-Wasserstein
Distributional Reduction: Unifying Dimensionality Reduction and Clustering with Gromov-Wasserstein
Hugues van Assel
Cédric Vincent-Cuaz
Nicolas Courty
Rémi Flamary
Pascal Frossard
Titouan Vayer
26
3
0
03 Feb 2024
Interpolating between Clustering and Dimensionality Reduction with
  Gromov-Wasserstein
Interpolating between Clustering and Dimensionality Reduction with Gromov-Wasserstein
Hugues van Assel
Cédric Vincent-Cuaz
Titouan Vayer
Rémi Flamary
Nicolas Courty
27
0
0
05 Oct 2023
Kernel-Based Testing for Single-Cell Differential Analysis
Kernel-Based Testing for Single-Cell Differential Analysis
Anthony Ozier-Lafontaine
Camille Fourneaux
G. Durif
Polina Arsenteva
C. Vallot
O. Gandrillon
Sandrine Giraud
Bertrand Michel
Franck Picard
29
5
0
17 Jul 2023
Matrix Information Theory for Self-Supervised Learning
Matrix Information Theory for Self-Supervised Learning
Yifan Zhang
Zhi-Hao Tan
Jingqin Yang
Weiran Huang
Yang Yuan
SSL
48
16
0
27 May 2023
SNEkhorn: Dimension Reduction with Symmetric Entropic Affinities
SNEkhorn: Dimension Reduction with Symmetric Entropic Affinities
Hugues van Assel
Titouan Vayer
Rémi Flamary
Nicolas Courty
25
9
0
23 May 2023
Contrastive Learning Is Spectral Clustering On Similarity Graph
Contrastive Learning Is Spectral Clustering On Similarity Graph
Zhi-Hao Tan
Yifan Zhang
Jingqin Yang
Yang Yuan
SSL
54
18
0
27 Mar 2023
Understanding How Dimension Reduction Tools Work: An Empirical Approach
  to Deciphering t-SNE, UMAP, TriMAP, and PaCMAP for Data Visualization
Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE, UMAP, TriMAP, and PaCMAP for Data Visualization
Yingfan Wang
Haiyang Huang
Cynthia Rudin
Yaron Shaposhnik
161
304
0
08 Dec 2020
1