3 papers
stat.ML2026
Beyond ReLU: How Activations Affect Neural Kernels and Random Wide Networks
David Holzmüller, Max Schölpple
In recent years, the neural tangent kernel (NTK) and neural network Gaussian process kernel (NNGP) have given theoreticians tractable limiting cases of fully connected neural netwo…
stat.ML2026
Self-Regularized Learning Methods
Max Schölpple, Liu Fanghui, Ingo Steinwart
We introduce a general framework for analyzing learning algorithms based on the notion of self-regularization, which captures implicit complexity control without requiring explicit…
math.ST2025
Schoenberg characterization of continuous non-stationary isotropic positive definite kernels
Felix Benning, Max David Schölpple
We characterize the continuous isotropic positive definite kernels on , where isotropy refers to invariance under the orthogonal group but not necessarily stat…