9 citations · 9 across the 3 of their papers we have counts for
4 papers
Bayesian Operator Learning: Posterior Existence and Convergence of Point Estimates for Gaussian Priors
Niklas Reinhardt, Jakob Zech
We develop a Bayesian framework for learning nonlinear operators between infinite-dimensional spaces. Given a map between separable Hilbert spaces,…
Statistical Learning Theory for Neural Operators
Niklas Reinhardt, Sven Wang, Jakob Zech
We present statistical convergence results for the learning of (possibly) non-linear mappings in infinite-dimensional spaces. Specifically, given a map $G_0:\mathcal X\to\mathcal Y…
Kinetic field theory: effects of modified gravity theories with screening mechanisms on non-linear cosmic density fluctuations
Alexander Oestreicher, Harshda Saxena, Niklas Reinhardt +3
In a mean-field approximation within Kinetic Field Theory, it is possible to derive an accurate analytic expression for the power spectrum of present-day non-linear cosmic density…
Type-II Zeeman slowing: Characterization and comparison to conventional radiative beam slowing schemes
Maurice Petzold, Paul Kaebert, Philipp Gersema +4
We describe a novel Zeeman slowing method reported in (Petzold et al (2018 New J. Phys. 20 042001)) and compare it to conventional radiative beam slowing schemes. The scheme is des…