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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
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Book ChapterDOI

Construction of Machine Learned Force Fields with Quantum Chemical Accuracy: Applications and Chemical Insights

Huziel E. Sauceda, +4 more
- 04 Jun 2020 - 
TL;DR: The hierarchical pathway from generating the dataset of reference calculations to the construction of the machine learning model, and the validation of the physics generated by the model are discussed, and empirical evidence that a higher level of theory generates a smoother PES is provided.
Journal ArticleDOI

Enhanced Performance of a Brain Switch by Simultaneous Use of EEG and NIRS Data for Asynchronous Brain-Computer Interface

Chang-Hee Han, +2 more
TL;DR: In this paper, the authors developed a hybrid EEG/NIRS brain switch and compared its performance with single modality EEG-and NIRS-based brain switch respectively, in terms of true positive rate (TPR), false positive rate(FPR), onset detection time (ODT), and information transfer rate (ITR).
Journal ArticleDOI

Autonomous robotic nanofabrication with reinforcement learning

Philipp Leinen, +9 more
- 27 Feb 2020 - 
TL;DR: This work demonstrates the potential of reinforcement learning (RL) in robotics by removing molecules autonomously with a scanning probe microscope from a supramolecular structure and reaches an excellent performance, enabling it to automate a task that previously had to be performed by a human.
Proceedings ArticleDOI

Classifying directions in continuous arm movement from EEG signals

Jeong-Seok Woo, +2 more
TL;DR: By the result of this study, the possibility of controlling neuro-prosthetics and evidence of neurological basis of the arm movement is confirmed and the directions of movement are classified.
Proceedings Article

Engineering Support Vector Machine Kerneis That Recognize Translation Initialion Sites.

Alexander Zien, +7 more
TL;DR: With the described techniques the recognition performance can be improved by 26% over leading existing approaches, and there is evidence that existing related methods could profit from advanced TIS recognition.