Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
2306.17638
Cited By
Geometric Autoencoders -- What You See is What You Decode
30 June 2023
Philipp Nazari
Sebastian Damrich
Fred Hamprecht
Re-assign community
ArXiv
PDF
HTML
Papers citing
"Geometric Autoencoders -- What You See is What You Decode"
10 / 10 papers shown
Title
Latent Manifold Reconstruction and Representation with Topological and Geometrical Regularization
Ren Wang
Pengcheng Zhou
39
0
0
07 May 2025
Investigating Image Manifolds of 3D Objects: Learning, Shape Analysis, and Comparisons
Benjamin Beaudett
Shenyuan Liang
Anuj Srivastava
58
0
0
09 Mar 2025
Random Forest Autoencoders for Guided Representation Learning
Adrien Aumon
Shuang Ni
Myriam Lizotte
Guy Wolf
Kevin R. Moon
Jake S. Rhodes
67
0
0
18 Feb 2025
Structure-preserving contrastive learning for spatial time series
Yiru Jiao
Sander van Cranenburgh
Simeon C. Calvert
H. Lint
AI4TS
97
0
0
10 Feb 2025
Proper Latent Decomposition
Daniel Kelshaw
Luca Magri
74
0
0
01 Dec 2024
Navigating the Effect of Parametrization for Dimensionality Reduction
Haiyang Huang
Yingfan Wang
Cynthia Rudin
81
1
0
24 Nov 2024
Metric Flow Matching for Smooth Interpolations on the Data Manifold
Kacper Kapusniak
Peter Potaptchik
Teodora Reu
Leo Zhang
Alexander Tong
Michael M. Bronstein
A. Bose
Francesco Di Giovanni
54
13
0
23 May 2024
Compressing Latent Space via Least Volume
Qiuyi Chen
M. Fuge
38
1
0
27 Apr 2024
InVA: Integrative Variational Autoencoder for Harmonization of Multi-modal Neuroimaging Data
Bowen Lei
Rajarshi Guhaniyogi
Krishnendu Chandra
Aaron Scheffler
Bani Mallick
20
0
0
05 Feb 2024
MMP++: Motion Manifold Primitives with Parametric Curve Models
Yonghyeon Lee
34
4
0
26 Oct 2023
1