collaborators

6 papers

stat.ML2026

Optimal Initialization in Depth: Lyapunov Initialization and Limit Theorems for Deep Leaky ReLU Networks

Constantin Kogler, Tassilo Schwarz, Samuel Kittle

Effective initialization in deep networks requires an understanding of random neural networks. In this work, a rigorous probabilistic analysis of deep bias-free random Leaky ReLU n…

stat.ML2026

Permutation-Invariant Spectral Learning via Dyson Diffusion

Tassilo Schwarz, Cai Dieball, Constantin Kogler +4

Diffusion models are central to generative modeling and have been adapted to graphs by diffusing adjacency matrix representations. The challenge of having up to such represent…

math.DS2026

Polynomial Tail Decay for Stationary Measures

Samuel Kittle, Constantin Kogler

We show on complete metric spaces a polynomial tail decay for stationary measures of contracting on average generating measures.

math.PR2026

Entropy Theory for Random Walks on Lie Groups

Samuel Kittle, Constantin Kogler

We develop entropy and variance results for the product of independent identically distributed random variables on Lie groups. Our results apply to the study of stationary measures…

math.DS2025

On absolute continuity of inhomogeneous and contracting on average self-similar measures

Samuel Kittle, Constantin Kogler

We give a condition for absolute continuity of self-similar measures in arbitrary dimensions. This allows us to construct the first explicit absolutely continuous examples of inhom…

math.DS2025

Dimension of contracting on average self-similar measures

Samuel Kittle, Constantin Kogler

We generalise Hochman's theorem on the dimension of self-similar measures to contracting on average measures and show that a weaker condition than exponential separation on all sca…