Only Bayes should learn a manifold (on the estimation of differential geometric structure from data)

13 June 2018

Papers citing "Only Bayes should learn a manifold (on the estimation of differential geometric structure from data)"

7 / 7 papers shown

Title
Pulling back symmetric Riemannian geometry for data analysis W. Diepeveen 29 2 0 11 Mar 2024
The Geometry of Neural Nets' Parameter Spaces Under Reparametrization Agustinus Kristiadi Felix Dangel Philipp Hennig 32 11 0 14 Feb 2023
Interpolation of Missing Swaption Volatility Data using Gibbs Sampling on Variational Autoencoders Ivo Richert R. Buch 32 1 0 21 Apr 2022
Geometric instability of out of distribution data across autoencoder architecture S. Agarwala Ben Dees Corey Lowman DRL 30 0 0 28 Jan 2022
Geometry-Aware Hamiltonian Variational Auto-Encoder Clément Chadebec Clément Mantoux S. Allassonnière DRL 24 15 0 22 Oct 2020
Variational Autoencoders with Riemannian Brownian Motion Priors Dimitris Kalatzis David Eklund Georgios Arvanitidis Søren Hauberg BDL DRL 60 48 0 12 Feb 2020
Expected path length on random manifolds David Eklund Søren Hauberg DRL 28 15 0 20 Aug 2019