Learning Flat Latent Manifolds with VAEs

12 February 2020

Patrick van der Smagt

DRL

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Papers citing "Learning Flat Latent Manifolds with VAEs"

28 / 28 papers shown

Title
Investigating Image Manifolds of 3D Objects: Learning, Shape Analysis, and Comparisons Benjamin Beaudett Shenyuan Liang Anuj Srivastava 53 0 0 09 Mar 2025
Understanding Variational Autoencoders with Intrinsic Dimension and Information Imbalance Charles Camboulin Diego Doimo Aldo Glielmo DRL 69 0 0 04 Nov 2024
Isometric Representation Learning for Disentangled Latent Space of Diffusion Models Jaehoon Hahm Junho Lee Sunghyun Kim Joonseok Lee DiffM 31 7 0 16 Jul 2024
Modularity aided consistent attributed graph clustering via coarsening Samarth Bhatia Yukti Makhija Manoj Kumar Sandeep Kumar 22 0 0 09 Jul 2024
Compressing Latent Space via Least Volume Qiuyi Chen M. Fuge 27 1 0 27 Apr 2024
Sequential Model for Predicting Patient Adherence in Subcutaneous Immunotherapy for Allergic Rhinitis Yin Li Yu Xiong Wenxin Fan Kai Wang Qingqing Yu Liping Si Patrick van der Smagt Jun Tang Nutan Chen 25 1 0 21 Jan 2024
Canonical normalizing flows for manifold learning Kyriakos Flouris E. Konukoglu DRL 48 7 0 19 Oct 2023
On Explicit Curvature Regularization in Deep Generative Models Yonghyeon Lee Frank C. Park BDL 22 12 0 19 Sep 2023
A Geometric Perspective on Autoencoders Yonghyeon Lee 16 6 0 15 Sep 2023
Geometric Autoencoders -- What You See is What You Decode Philipp Nazari Sebastian Damrich Fred Hamprecht 30 12 0 30 Jun 2023
Data Representations' Study of Latent Image Manifolds Ilya Kaufman Omri Azencot 8 7 0 31 May 2023
Computationally-Efficient Neural Image Compression with Shallow Decoders Yibo Yang Stephan Mandt 11 22 0 13 Apr 2023
VTAE: Variational Transformer Autoencoder with Manifolds Learning Pourya Shamsolmoali Masoumeh Zareapoor Huiyu Zhou Dacheng Tao Xuelong Li DRL 20 11 0 03 Apr 2023
Manifold Learning by Mixture Models of VAEs for Inverse Problems Giovanni S. Alberti J. Hertrich Matteo Santacesaria Silvia Sciutto DRL 29 6 0 27 Mar 2023
Amortized Variational Inference: A Systematic Review Ankush Ganguly Sanjana Jain Ukrit Watchareeruetai 20 14 0 22 Sep 2022
Adversarial robustness of VAEs through the lens of local geometry Asif Khan Amos Storkey AAML DRL 18 2 0 08 Aug 2022
GD-VAEs: Geometric Dynamic Variational Autoencoders for Learning Nonlinear Dynamics and Dimension Reductions Ryan Lopez P. Atzberger AI4CE 24 7 0 10 Jun 2022
Discriminating Against Unrealistic Interpolations in Generative Adversarial Networks Henning Petzka Ted Kronvall C. Sminchisescu GAN 18 2 0 02 Mar 2022
Flat Latent Manifolds for Human-machine Co-creation of Music Nutan Chen Djalel Benbouzid Francesco Ferroni Mathis Nitschke Luciano Pinna Patrick van der Smagt 11 0 0 23 Feb 2022
Exploring the Latent Space of Autoencoders with Interventional Assays Felix Leeb Stefan Bauer M. Besserve Bernhard Schölkopf DRL 43 17 0 30 Jun 2021
Local Disentanglement in Variational Auto-Encoders Using Jacobian $L_1$ Regularization Travers Rhodes Daniel D. Lee DRL 11 15 0 05 Jun 2021
Out-of-distribution Detection and Generation using Soft Brownian Offset Sampling and Autoencoders Felix Möller Diego Botache Denis Huseljic Florian Heidecker Maarten Bieshaar Bernhard Sick OODD 11 25 0 04 May 2021
Uncertainty Estimation Using Riemannian Model Dynamics for Offline Reinforcement Learning Guy Tennenholtz Shie Mannor OffRL 13 11 0 22 Feb 2021
Variational Autoencoders for Learning Nonlinear Dynamics of Physical Systems Ryan Lopez P. Atzberger DRL AI4CE 17 13 0 07 Dec 2020
On Implicit Regularization in $β$ -VAEs Abhishek Kumar Ben Poole DRL 10 53 0 31 Jan 2020
Deep Cosine Metric Learning for Person Re-Identification N. Wojke Alex Bewley 31 352 0 02 Dec 2018
Simple Online and Realtime Tracking with a Deep Association Metric N. Wojke Alex Bewley Dietrich Paulus VOT 228 3,463 0 21 Mar 2017
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 247 3,236 0 24 Nov 2016