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His research interest is in the field of machine learning, deep learning and data analysis covering a wide range of theory and numerous scientific (Physics, Chemistry and Neuroscience) and industrial applications. GS > 69000, h 114. His research areas include statistical learning theory for neural networks, support vector machines and ensemble learning techniques. He contributed to the field of signal processing working on time-series analysis, statistical denoising methods and blind source separation. His present application interests are expanded to the analysis of biomedical data, most recently to brain computer interfacing, genomic data analysis, computational chemistry and atomistic simulations.
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论文共 771 篇作者统计合作学者相似作者
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Dilyara Bareeva,Marina M. -C. Höhne,Alexander Warnecke,Lukas Pirch,Klaus-Robert Müller,Konrad Rieck, Kirill Bykov
CoRR (2024)
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ENERGY AND AI (2024): 100328
IEEE transactions on pattern analysis and machine intelligenceno. 5 (2024): 3257-3274
Frederick Klauschen, Jonas Dippel,Philipp Keyl,Philipp Jurmeister,Michael Bockmayr,Andreas Mock, Oliver Buchstab,Maximilian Alber,Lukas Ruff,Grégoire Montavon,Klaus-Robert Müller
Pathologie (Heidelberg, Germany)no. 2 (2024): 133-139
Frederick Klauschen, Jonas Dippel, Philipp Keyl,Philipp Jurmeister,Michael Bockmayr,Andreas Mock, Oliver Buchstab,Maximilian Alber,Lukas Ruff,Gregoire Montavon,Klaus-Robert Mueller
ANNUAL REVIEW OF PATHOLOGY-MECHANISMS OF DISEASEno. 1 (2024): 541-570
IEEE transactions on pattern analysis and machine intelligenceno. 99 (2024): 1-18
Jonas Dippel, Barbara Feulner, Tobias Winterhoff,Simon Schallenberg, Gabriel Dernbach, Andreas Kunft, Stephan Tietz, Timo Milbich, Simon Heinke, Marie-Lisa Eich, Julika Ribbat-Idel, Rosemarie Krupar,
arxiv(2024)
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Frederick Klauschen, Jonas Dippel,Philipp Keyl,Philipp Jurmeister,Michael Bockmayr,Andreas Mock, Oliver Buchstab,Maximilian Alber,Lukas Ruff,Grégoire Montavon,Klaus-Robert Müller
Die Pathologieno. 2 (2024): 133-139
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