7 citations · 8 across the 3 of their papers we have counts for
4 papers · 1 filter
A kernel-based approach to molecular conformation analysis
Stefan Klus, Andreas Bittracher, Ingmar Schuster +1
We present a novel machine learning approach to understanding conformation dynamics of biomolecules. The approach combines kernel-based techniques that are popular in the machine l…
Singular Value Decomposition of Operators on Reproducing Kernel Hilbert Spaces
Mattes Mollenhauer, Ingmar Schuster, Stefan Klus +1
Reproducing kernel Hilbert spaces (RKHSs) play an important role in many statistics and machine learning applications ranging from support vector machines to Gaussian processes and…
Analyzing high-dimensional time-series data using kernel transfer operator eigenfunctions
Stefan Klus, Sebastian Peitz, Ingmar Schuster
Kernel transfer operators, which can be regarded as approximations of transfer operators such as the Perron-Frobenius or Koopman operator in reproducing kernel Hilbert spaces, are…
Markov Chain Importance Sampling -- a highly efficient estimator for MCMC
Ingmar Schuster, Ilja Klebanov
Markov chain (MC) algorithms are ubiquitous in machine learning and statistics and many other disciplines. Typically, these algorithms can be formulated as acceptance rejection met…