Klaus‐Robert Müller

Nonlinear Component Analysis as a Kernel Eigenvalue Problem

A new method for performing a nonlinear form of principal component analysis is proposed. By the use of integral operator kernel functions, one can efficiently compute principal...

Efficient BackProp

Methods for interpreting and understanding deep neural networks

How to Explain Individual Classification Decisions

After building a classifier with modern tools of machine learning we typically have a black box at hand that is able to predict well for unseen data. Thus, we get an answer to t...

The connection between regularization operators and support vector kernels

Explainable AI: Interpreting, Explaining and Visualizing Deep Learning

Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications

With the broader and highly successful usage of machine learning (ML) in industry and the sciences, there has been a growing demand for explainable artificial intelligence (XAI)...