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Learning Topology-Preserving Data Representations
v1v2 (latest)

Learning Topology-Preserving Data Representations

31 January 2023
I. Trofimov
D. Cherniavskii
Eduard Tulchinskii
Nikita Balabin
Evgeny Burnaev
S. Barannikov
ArXiv (abs)PDFHTML

Papers citing "Learning Topology-Preserving Data Representations"

6 / 6 papers shown
Title
Torsion in Persistent Homology and Neural Networks
Torsion in Persistent Homology and Neural Networks
Maria Walch
44
0
0
03 Jun 2025
Latent Manifold Reconstruction and Representation with Topological and Geometrical Regularization
Latent Manifold Reconstruction and Representation with Topological and Geometrical Regularization
Ren Wang
Pengcheng Zhou
74
0
0
07 May 2025
Structure-preserving contrastive learning for spatial time series
Structure-preserving contrastive learning for spatial time series
Yiru Jiao
Sander van Cranenburgh
Simeon C. Calvert
H. Lint
AI4TS
168
0
0
10 Feb 2025
Relative Representations: Topological and Geometric Perspectives
Relative Representations: Topological and Geometric Perspectives
Alejandro García-Castellanos
Giovanni Luca Marchetti
Danica Kragic
Martina Scolamiero
116
1
0
17 Sep 2024
Disentanglement Learning via Topology
Disentanglement Learning via Topology
Nikita Balabin
Daria Voronkova
I. Trofimov
Evgeny Burnaev
S. Barannikov
DRL
152
3
0
24 Aug 2023
Data Topology-Dependent Upper Bounds of Neural Network Widths
Data Topology-Dependent Upper Bounds of Neural Network Widths
Sangmin Lee
Jong Chul Ye
80
1
0
25 May 2023
1