21 citations · 23 across the 4 of their papers we have counts for
4 papers · 1 filter
Whitening Convergence Rate of Coupling-based Normalizing Flows
Felix Draxler, Christoph Schnörr, Ullrich Köthe
Coupling-based normalizing flows (e.g. RealNVP) are a popular family of normalizing flow architectures that work surprisingly well in practice. This calls for theoretical understan…
Learning System Parameters from Turing Patterns
David Schnörr, Christoph Schnörr
The Turing mechanism describes the emergence of spatial patterns due to spontaneous symmetry breaking in reaction-diffusion processes and underlies many developmental processes. Id…
Self-Assignment Flows for Unsupervised Data Labeling on Graphs
Matthias Zisler, Artjom Zern, Stefania Petra +1
This paper extends the recently introduced assignment flow approach for supervised image labeling to unsupervised scenarios where no labels are given. The resulting self-assignment…
Unsupervised Assignment Flow: Label Learning on Feature Manifolds by Spatially Regularized Geometric Assignment
Artjom Zern, Matthias Zisler, Stefania Petra +1
This paper introduces the unsupervised assignment flow that couples the assignment flow for supervised image labeling with Riemannian gradient flows for label evolution on feature…