2 citations · 2 across the 2 of their papers we have counts for
4 papers
Stochastic Image Deformation in Frequency Domain and Parameter Estimation using Moment Evolutions
Line Kühnel, Alexis Arnaudon, Tom Fletcher +1
Modelling deformation of anatomical objects observed in medical images can help describe disease progression patterns and variations in anatomy across populations. We apply a stoch…
Latent Space Non-Linear Statistics
Line Kuhnel, Tom Fletcher, Sarang Joshi +1
Given data, deep generative models, such as variational autoencoders (VAE) and generative adversarial networks (GAN), train a lower dimensional latent representation of the data sp…
Differential geometry and stochastic dynamics with deep learning numerics
Line Kühnel, Alexis Arnaudon, Stefan Sommer
In this paper, we demonstrate how deterministic and stochastic dynamics on manifolds, as well as differential geometric constructions can be implemented concisely and efficiently u…
Stochastic Development Regression on Non-Linear Manifolds
Line Kühnel, Stefan Sommer
We introduce a regression model for data on non-linear manifolds. The model describes the relation between a set of manifold valued observations, such as shapes of anatomical objec…