48 citations · 192 across the 16 of their papers we have counts for
3 papers · 1 filter
A PAC-Bayes oracle inequality for sparse neural networks
Maximilian F. Steffen, Mathias Trabs
We study the Gibbs posterior distribution for sparse deep neural nets in a nonparametric regression setting. The posterior can be accessed via Metropolis-adjusted Langevin algorith…
Dimensionality Reduction and Wasserstein Stability for Kernel Regression
Stephan Eckstein, Armin Iske, Mathias Trabs
In a high-dimensional regression framework, we study consequences of the naive two-step procedure where first the dimension of the input variables is reduced and second, the reduce…
Calomplification -- The Power of Generative Calorimeter Models
Sebastian Bieringer, Anja Butter, Sascha Diefenbacher +7
Motivated by the high computational costs of classical simulations, machine-learned generative models can be extremely useful in particle physics and elsewhere. They become especia…