K
Klaus-Robert Müller
Researcher at Technical University of Berlin
Publications - 799
Citations - 98394
Klaus-Robert Müller is an academic researcher from Technical University of Berlin. The author has contributed to research in topics: Artificial neural network & Computer science. The author has an hindex of 129, co-authored 764 publications receiving 79391 citations. Previous affiliations of Klaus-Robert Müller include Korea University & University of Tokyo.
Papers
More filters
Posted Content
Understanding Machine-learned Density Functionals
Li Li,John C. Snyder,John C. Snyder,Isabelle M. Pelaschier,Isabelle M. Pelaschier,Jessica Huang,Uma Naresh Niranjan,Paul Duncan,Matthias Rupp,Klaus-Robert Müller,Klaus-Robert Müller,Kieron Burke +11 more
TL;DR: In this article, kernel ridge regression is used to approximate the kinetic energy of non-interacting fermions in a one-dimensional box as a functional of their density, and the properties of different kernels and methods of cross-validation are explored.
Journal ArticleDOI
Artificial intelligence and pathology: From principles to practice and future applications in histomorphology and molecular profiling.
Albrecht Stenzinger,Albrecht Stenzinger,Albrecht Stenzinger,Maximilian Alber,Frederick Klauschen,Ray Jones,Michael Allgäuer,Philipp Jurmeister,Michael Bockmayr,Jan Budczies,Jochen K. Lennerz,Johannes Eschrich,Daniel Kazdal,Peter Schirmacher,Alex H. Wagner,Frank Tacke,David Capper,Klaus-Robert Müller,Frederick Klauschen,Frederick Klauschen,Frederick Klauschen +20 more
TL;DR: In this article, the authors review the pertinent literature of AI methods and their applications to pathology, and put the current achievements and what can be expected in the future in the context of the requirements for research and routine diagnostics.
Journal ArticleDOI
Improved decoding of neural activity from fMRI signals using non-separable spatiotemporal deconvolutions
Felix Bießmann,Yusuke Murayama,Nikos K. Logothetis,Nikos K. Logothetis,Klaus-Robert Müller,Frank C. Meinecke +5 more
TL;DR: Results show that abandoning the spatiotemporal separability assumption consistently improves the decoding accuracy of neural signals from fMRI data, and are compared with results from optical imaging and fMRI studies.
Journal ArticleDOI
Noise robust estimates of correlation dimension and K2 entropy.
TL;DR: Using Gaussian kernels to define the correlation sum, it is shown theoretically that the estimates, which are derived for additive white Gaussian noise, are also robust for moderately colored noise and underline the usefulness of the proposed correction schemes.
Journal ArticleDOI
Directional Variance Adjustment: Bias Reduction in Covariance Matrices Based on Factor Analysis with an Application to Portfolio Optimization
Daniel Bartz,Kerr Hatrick,Christian W. Hesse,Klaus-Robert Müller,Klaus-Robert Müller,Steven Lemm +5 more
TL;DR: In a thorough empirical study for the US, European, and Hong Kong stock market, it is shown that the proposed method leads to improved portfolio allocation and introduces the Directional Variance Adjustment (DVA) algorithm, which diminishes the systematic error.