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Learning Manifold Dimensions with Conditional Variational Autoencoders

Learning Manifold Dimensions with Conditional Variational Autoencoders

23 February 2023
Yijia Zheng
Tong He
Yixuan Qiu
David Wipf
    DRL
ArXivPDFHTML

Papers citing "Learning Manifold Dimensions with Conditional Variational Autoencoders"

10 / 10 papers shown
Title
Deep Generative Models: Complexity, Dimensionality, and Approximation
Deep Generative Models: Complexity, Dimensionality, and Approximation
Kevin Wang
Hongqian Niu
Yixin Wang
Didong Li
DRL
41
0
0
01 Apr 2025
Reducing Class-wise Confusion for Incremental Learning with Disentangled Manifolds
Reducing Class-wise Confusion for Incremental Learning with Disentangled Manifolds
Huitong Chen
Yu Wang
Yan Fan
Guosong Jiang
Q. Hu
CLL
46
0
0
22 Mar 2025
A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation
A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation
M. Valiuddin
R. V. Sloun
C.G.A. Viviers
Peter H. N. de With
Fons van der Sommen
UQCV
91
1
0
25 Nov 2024
A Geometric Framework for Understanding Memorization in Generative Models
A Geometric Framework for Understanding Memorization in Generative Models
Brendan Leigh Ross
Hamidreza Kamkari
Tongzi Wu
Rasa Hosseinzadeh
Zhaoyan Liu
George Stein
Jesse C. Cresswell
G. Loaiza-Ganem
61
6
0
31 Oct 2024
A Wiener process perspective on local intrinsic dimension estimation
  methods
A Wiener process perspective on local intrinsic dimension estimation methods
Piotr Tempczyk
Łukasz Garncarek
Dominik Filipiak
Adam Kurpisz
44
1
0
24 Jun 2024
A Geometric View of Data Complexity: Efficient Local Intrinsic Dimension
  Estimation with Diffusion Models
A Geometric View of Data Complexity: Efficient Local Intrinsic Dimension Estimation with Diffusion Models
Hamidreza Kamkari
Brendan Leigh Ross
Rasa Hosseinzadeh
Jesse C. Cresswell
G. Loaiza-Ganem
DiffM
42
11
0
05 Jun 2024
Investigating and Improving Latent Density Segmentation Models for
  Aleatoric Uncertainty Quantification in Medical Imaging
Investigating and Improving Latent Density Segmentation Models for Aleatoric Uncertainty Quantification in Medical Imaging
M. Valiuddin
Christiaan G. A. Viviers
R. V. Sloun
Peter H. N. de With
Fons van der Sommen
UQCV
39
2
0
31 Jul 2023
From NeurODEs to AutoencODEs: a mean-field control framework for
  width-varying Neural Networks
From NeurODEs to AutoencODEs: a mean-field control framework for width-varying Neural Networks
Cristina Cipriani
M. Fornasier
Alessandro Scagliotti
AI4CE
16
5
0
05 Jul 2023
Neural Implicit Manifold Learning for Topology-Aware Density Estimation
Neural Implicit Manifold Learning for Topology-Aware Density Estimation
Brendan Leigh Ross
G. Loaiza-Ganem
Anthony L. Caterini
Jesse C. Cresswell
AI4CE
33
2
0
22 Jun 2022
The Intrinsic Dimension of Images and Its Impact on Learning
The Intrinsic Dimension of Images and Its Impact on Learning
Phillip E. Pope
Chen Zhu
Ahmed Abdelkader
Micah Goldblum
Tom Goldstein
197
261
0
18 Apr 2021
1