Symmetric and antisymmetric kernels for machine learning problems in quantum physics and chemistry

no code implementations • 31 Mar 2021 • Stefan Klus, Patrick Gelß, Feliks Nüske, Frank Noé

We derive symmetric and antisymmetric kernels by symmetrizing and antisymmetrizing conventional kernels and analyze their properties.

BIG-bench Machine Learning

Feature space approximation for kernel-based supervised learning

1 code implementation • 25 Nov 2020 • Patrick Gelß, Stefan Klus, Ingmar Schuster, Christof Schütte

We propose a method for the approximation of high- or even infinite-dimensional feature vectors, which play an important role in supervised learning.

regression Time Series +1

Tensor-based algorithms for image classification

1 code implementation • 4 Oct 2019 • Stefan Klus, Patrick Gelß

The interest in machine learning with tensor networks has been growing rapidly in recent years.

BIG-bench Machine Learning Classification +4

Tensor-based computation of metastable and coherent sets

1 code implementation • 12 Aug 2019 • Feliks Nüske, Patrick Gelß, Stefan Klus, Cecilia Clementi

Recent years have seen rapid advances in the data-driven analysis of dynamical systems based on Koopman operator theory and related approaches.