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Pulling back information geometry
v1v2 (latest)

Pulling back information geometry

International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
9 June 2021
Georgios Arvanitidis
Miguel González Duque
Alison Pouplin
Dimitris Kalatzis
Søren Hauberg
    DRL
ArXiv (abs)PDFHTML

Papers citing "Pulling back information geometry"

14 / 14 papers shown
Geodesic Calculus on Implicitly Defined Latent Manifolds
Geodesic Calculus on Implicitly Defined Latent Manifolds
Florine Hartwig
Josua Sassen
Juliane Braunsmann
M. Rumpf
B. Wirth
162
0
0
10 Oct 2025
Riemannian-Geometric Fingerprints of Generative Models
Riemannian-Geometric Fingerprints of Generative Models
Hae Jin Song
Laurent Itti
217
7
0
28 Jun 2025
Connecting Neural Models Latent Geometries with Relative Geodesic Representations
Connecting Neural Models Latent Geometries with Relative Geodesic Representations
Hanlin Yu
Berfin Inal
Georgios Arvanitidis
Soren Hauberg
Francesco Locatello
Marco Fumero
DRL
509
2
0
02 Jun 2025
Follow the Energy, Find the Path: Riemannian Metrics from Energy-Based Models
Follow the Energy, Find the Path: Riemannian Metrics from Energy-Based Models
Louis Bethune
David Vigouroux
Yilun Du
Rufin VanRullen
Thomas Serre
Victor Boutin
DiffM
641
3
0
23 May 2025
The Spacetime of Diffusion Models: An Information Geometry Perspective
The Spacetime of Diffusion Models: An Information Geometry Perspective
Rafał Karczewski
Markus Heinonen
Alison Pouplin
Søren Hauberg
Vikas Garg
DiffM
366
1
0
23 May 2025
Decoder ensembling for learned latent geometries
Decoder ensembling for learned latent geometries
Stas Syrota
Pablo Moreno-Muñoz
Søren Hauberg
DRLAI4CE
309
7
0
14 Aug 2024
Metric Flow Matching for Smooth Interpolations on the Data Manifold
Metric Flow Matching for Smooth Interpolations on the Data ManifoldNeural Information Processing Systems (NeurIPS), 2024
Kacper Kapusniak
Peter Potaptchik
Teodora Reu
Leo Zhang
Alexander Tong
Michael M. Bronstein
A. Bose
Francesco Di Giovanni
367
54
0
23 May 2024
Bayesian Unsupervised Disentanglement of Anatomy and Geometry for Deep Groupwise Image Registration
Bayesian Unsupervised Disentanglement of Anatomy and Geometry for Deep Groupwise Image RegistrationIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024
Xinzhe Luo
Xin Wang
Linda Shapiro
Chun Yuan
Jianfeng Feng
Xiahai Zhuang
401
0
0
04 Jan 2024
On Closed-Form Expressions for the Fisher-Rao Distance
On Closed-Form Expressions for the Fisher-Rao Distance
Henrique K. Miyamoto
Fábio C. C. Meneghetti
Julianna Pinele
Sueli I. R. Costa
312
27
0
28 Apr 2023
Identifying latent distances with Finslerian geometry
Identifying latent distances with Finslerian geometry
Alison Pouplin
David Eklund
Carl Henrik Ek
Søren Hauberg
370
2
0
20 Dec 2022
The Fisher-Rao Loss for Learning under Label Noise
The Fisher-Rao Loss for Learning under Label NoiseInformation Geometry (IG), 2022
Henrique K. Miyamoto
Fábio C. C. Meneghetti
Sueli I. R. Costa
NoLa
270
6
0
28 Oct 2022
Hyperbolic VAE via Latent Gaussian Distributions
Hyperbolic VAE via Latent Gaussian DistributionsNeural Information Processing Systems (NeurIPS), 2022
Seunghyuk Cho
Juyong Lee
Dongwoo Kim
DRL
445
15
0
30 Sep 2022
Mario Plays on a Manifold: Generating Functional Content in Latent Space
  through Differential Geometry
Mario Plays on a Manifold: Generating Functional Content in Latent Space through Differential Geometry
Miguel González Duque
Rasmus Berg Palm
Søren Hauberg
S. Risi
DiffM
249
7
0
31 May 2022
Detecting Model Misspecification in Amortized Bayesian Inference with
  Neural Networks
Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks
Marvin Schmitt
Paul-Christian Bürkner
Ullrich Kothe
Stefan T. Radev
452
56
0
16 Dec 2021
1
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