Latent Space Oddity: on the Curvature of Deep Generative Models

31 October 2017

Papers citing "Latent Space Oddity: on the Curvature of Deep Generative Models"

50 / 60 papers shown

Title
Image Interpolation with Score-based Riemannian Metrics of Diffusion Models Shinnosuke Saito Takashi Matsubara DiffM 82 1 0 28 Apr 2025
A group-theoretic framework for machine learning in hyperbolic spaces Vladimir Jaćimović 54 0 0 12 Jan 2025
On Probabilistic Pullback Metrics for Latent Hyperbolic Manifolds Luis Augenstein Noémie Jaquier Tamim Asfour Leonel Rozo 33 0 0 28 Oct 2024
Beyond Flatland: A Geometric Take on Matching Methods for Treatment Effect Estimation Melanie F. Pradier Javier González CML 50 0 0 09 Sep 2024
Varying Manifolds in Diffusion: From Time-varying Geometries to Visual Saliency Junhao Chen Manyi Li Zherong Pan Xifeng Gao Changhe Tu DiffM 43 2 0 07 Jun 2024
Manifold Integrated Gradients: Riemannian Geometry for Feature Attribution Eslam Zaher Maciej Trzaskowski Quan Nguyen Fred Roosta AAML 29 4 0 16 May 2024
Tilt your Head: Activating the Hidden Spatial-Invariance of Classifiers Johann Schmidt Sebastian Stober 48 1 0 06 May 2024
Pulling back symmetric Riemannian geometry for data analysis W. Diepeveen 32 2 0 11 Mar 2024
Understanding the Latent Space of Diffusion Models through the Lens of Riemannian Geometry Yong-Hyun Park Mingi Kwon J. Choi Junghyo Jo Youngjung Uh DiffM 40 60 0 24 Jul 2023
Data Representations' Study of Latent Image Manifolds Ilya Kaufman Omri Azencot 14 7 0 31 May 2023
Geometric constraints improve inference of sparsely observed stochastic dynamics Dimitra Maoutsa AI4CE 30 3 0 02 Apr 2023
Directional Connectivity-based Segmentation of Medical Images Ziyun Yang Sina Farsiu 38 36 0 31 Mar 2023
Variational Inference for Longitudinal Data Using Normalizing Flows Clément Chadebec S. Allassonnière BDL DRL 31 1 0 24 Mar 2023
Unsupervised Discovery of Semantic Latent Directions in Diffusion Models Yong-Hyun Park Mingi Kwon Junghyo Jo Youngjung Uh DiffM 41 22 0 24 Feb 2023
The Geometry of Neural Nets' Parameter Spaces Under Reparametrization Agustinus Kristiadi Felix Dangel Philipp Hennig 32 11 0 14 Feb 2023
Geometric path augmentation for inference of sparsely observed stochastic nonlinear systems Dimitra Maoutsa 32 1 0 19 Jan 2023
Deep Curvilinear Editing: Commutative and Nonlinear Image Manipulation for Pretrained Deep Generative Model Takehiro Aoshima Takashi Matsubara 47 4 0 26 Nov 2022
Neural Conservation Laws: A Divergence-Free Perspective Jack Richter-Powell Y. Lipman Ricky T. Q. Chen 56 51 0 04 Oct 2022
Smooth image-to-image translations with latent space interpolations Yahui Liu E. Sangineto Yajing Chen Linchao Bao Haoxian Zhang N. Sebe Bruno Lepri Marco De Nadai 48 2 0 03 Oct 2022
A Geometric Perspective on Variational Autoencoders Clément Chadebec S. Allassonnière DRL 42 21 0 15 Sep 2022
Separable Shape Tensors for Aerodynamic Design Zach Grey O. Doronina Andrew Glaws 21 7 0 04 Aug 2022
Video2StyleGAN: Encoding Video in Latent Space for Manipulation Ji-yang Yu Jingen Liu Jing-ling Huang Wei Zhang Tao Mei CVBM 34 0 0 27 Jun 2022
Pythae: Unifying Generative Autoencoders in Python -- A Benchmarking Use Case Clément Chadebec Louis J. Vincent S. Allassonnière DRL 39 29 0 16 Jun 2022
GD-VAEs: Geometric Dynamic Variational Autoencoders for Learning Nonlinear Dynamics and Dimension Reductions Ryan Lopez P. Atzberger AI4CE 37 8 0 10 Jun 2022
Interpolation of Missing Swaption Volatility Data using Gibbs Sampling on Variational Autoencoders Ivo Richert R. Buch 32 1 0 21 Apr 2022
Autoencoding Low-Resolution MRI for Semantically Smooth Interpolation of Anisotropic MRI Jörg Sander B. D. de Vos Ivana Ivsgum DiffM MedIm 13 15 0 18 Feb 2022
Lagrangian Manifold Monte Carlo on Monge Patches M. Hartmann Mark Girolami Arto Klami 18 10 0 01 Feb 2022
Geometric instability of out of distribution data across autoencoder architecture S. Agarwala Ben Dees Corey Lowman DRL 30 0 0 28 Jan 2022
Rayleigh EigenDirections (REDs): GAN latent space traversals for multidimensional features Guha Balakrishnan Raghudeep Gadde Aleix M. Martinez Pietro Perona 46 3 0 25 Jan 2022
Multi-Asset Spot and Option Market Simulation Magnus Wiese Ben Wood Alexandre Pachoud R. Korn Hans Buehler Phillip Murray Lianjun Bai 27 21 0 13 Dec 2021
Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples Kanghyun Choi Deokki Hong Noseong Park Youngsok Kim Jinho Lee MQ 27 64 0 04 Nov 2021
Exploring the Latent Space of Autoencoders with Interventional Assays Felix Leeb Stefan Bauer M. Besserve Bernhard Schölkopf DRL 54 17 0 30 Jun 2021
Smoothing the Disentangled Latent Style Space for Unsupervised Image-to-Image Translation Yahui Liu E. Sangineto Yajing Chen Linchao Bao Haoxian Zhang N. Sebe Bruno Lepri Wei Wang Marco De Nadai DRL 48 44 0 16 Jun 2021
Pulling back information geometry Georgios Arvanitidis Miguel González Duque Alison Pouplin Dimitris Kalatzis Søren Hauberg DRL 30 14 0 09 Jun 2021
On Linear Interpolation in the Latent Space of Deep Generative Models M. Michelis Quentin Becker 29 11 0 08 May 2021
Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder Clément Chadebec Elina Thibeau-Sutre Ninon Burgos S. Allassonnière 48 63 0 30 Apr 2021
Data Augmentation with Variational Autoencoders and Manifold Sampling Clément Chadebec S. Allassonnière DRL 18 23 0 25 Mar 2021
Bayesian Quadrature on Riemannian Data Manifolds Christian Frohlich A. Gessner Philipp Hennig Bernhard Schölkopf Georgios Arvanitidis 29 4 0 12 Feb 2021
LaSeSOM: A Latent and Semantic Representation Framework for Soft Object Manipulation Peng Zhou Jihong Zhu Shengzeng Huo D. Navarro-Alarcon 27 32 0 10 Dec 2020
Illumination Normalization by Partially Impossible Encoder-Decoder Cost Function S. Cruz B. Taetz Thomas Stifter D. Stricker DiffM 22 3 0 06 Nov 2020
Mixing Consistent Deep Clustering D. Lutscher Ali el Hassouni M. Stol Mark Hoogendoorn SSL 19 2 0 03 Nov 2020
Geometry-Aware Hamiltonian Variational Auto-Encoder Clément Chadebec Clément Mantoux S. Allassonnière DRL 24 15 0 22 Oct 2020
Principled Interpolation in Normalizing Flows Samuel G. Fadel Sebastian Mair Ricardo da S. Torres Ulf Brefeld 83 3 0 22 Oct 2020
Generative models with kernel distance in data space Szymon Knop Marcin Mazur Przemysław Spurek Jacek Tabor Igor T. Podolak GAN SyDa 27 11 0 15 Sep 2020
Geometrically Enriched Latent Spaces Georgios Arvanitidis Søren Hauberg Bernhard Schölkopf DRL 19 51 0 02 Aug 2020
Variational Autoencoder with Learned Latent Structure Marissa Connor Gregory H. Canal Christopher Rozell CML DRL 34 42 0 18 Jun 2020
Manifold GPLVMs for discovering non-Euclidean latent structure in neural data Kristopher T. Jensen Ta-Chu Kao Marco Tripodi Guillaume Hennequin DRL 22 31 0 12 Jun 2020
Variational Autoencoders with Riemannian Brownian Motion Priors Dimitris Kalatzis David Eklund Georgios Arvanitidis Søren Hauberg BDL DRL 60 48 0 12 Feb 2020
Learning Flat Latent Manifolds with VAEs Nutan Chen Alexej Klushyn Francesco Ferroni Justin Bayer Patrick van der Smagt DRL 35 39 0 12 Feb 2020
Quantum device fine-tuning using unsupervised embedding learning N. V. Esbroeck D. Lennon H. Moon Vu-Linh Nguyen F. Vigneau ... L. Yu D. Zumbuhl G. Briggs D. Sejdinovic N. Ares 16 29 0 13 Jan 2020