Felix Biessmann

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Citations	2726	2060
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i10-index	31	26

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Klaus-Robert MüllerTU Berlin & Korea University & Google Brain & MPIIVerified email at tu-berlin.de
Sebastian SchelterAssistant Professor at University of AmsterdamVerified email at uva.nl
Sven DähneAmazonVerified email at amazon.com
Philipp SchmidtAmazonVerified email at amazon.com
Dustin LangeStealth mode (ex Amazon)Verified email at sent.com
Stefan HaufeTechnische Universität Berlin, Physikalisch-Technische Bundesanstalt, Charité - UniversitätsmedizinVerified email at tu-berlin.de
Tammo RukatAmazon ResearchVerified email at amazon.com
Kai GörgenBCCN BerlinVerified email at bccn-berlin.de
Benjamin BlankertzTechnische Universität Berlin, Neurotechnology groupVerified email at tu-berlin.de
Siamac FazliNazarbayev UniversityVerified email at nu.edu.kz
Nikos LogothetisVisiting Professor of Neuroscience, Stanford UniversityVerified email at stanford.edu
John-Dylan HaynesProfessor for Theory and Analysis of Large-Scale Brain Signals, Charite - Universitätsmedizin Berlin, GermanyVerified email at bccn-berlin.de
Gregor RainerProfessor, University of FribourgVerified email at unifr.ch
Janne M. HahneUniversity Medical Center, Georg-August University GoettingenVerified email at bccn.uni-goettingen.de
Ning JiangWest China Hospital, Sichuan UniversityVerified email at ieee.org
Prof. Dr. Dario FarinaProfessor and Chair in Neurorehabilitation Engineering, Dept. Bioengineering, Imperial CollegeVerified email at imperial.ac.uk
Lucas C. ParraProfessor of Biomedical Engineering, City College of New York, CUNYVerified email at ccny.cuny.edu
Hubertus RehbaumDr. Rehbaum Technology Consulting GmbHVerified email at rehbaum.info
David SalinasAmazonVerified email at ens-lyon.org
Wojciech SamekProfessor at TU Berlin, Head of AI Department at Fraunhofer HHI, BIFOLD FellowVerified email at hhi.fraunhofer.de

Felix Biessmann

Einstein Center Digital Future, Beuth Hochschule für Technik

Verified email at beuth-hochschule.de - Homepage

Machine Learning


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On the interpretation of weight vectors of linear models in multivariate neuroimaging S Haufe, F Meinecke, K Görgen, S Dähne, JD Haynes, B Blankertz, ... Neuroimage 87, 96-110, 2014	906	2014
Linear and nonlinear regression techniques for simultaneous and proportional myoelectric control JM Hahne, F Biessmann, N Jiang, H Rehbaum, D Farina, FC Meinecke, ... Neural Systems and Rehabilitation Engineering, IEEE Transactions on 22 (2 …, 2014	323	2014
Analysis of Multimodal Neuroimaging Data F Bießmann, S Plis, FC Meinecke, T Eichele, KR Müller IEEE Reviews in Biomedical Engineering 4, 26 - 58, 2011	156	2011
Automating large-scale data quality verification S Schelter, D Lange, P Schmidt, M Celikel, F Biessmann, A Grafberger Proceedings of the VLDB Endowment 11 (12), 1781-1794, 2018	122	2018
Decoding Three-Dimensional Trajectory of Executed and Imagined Arm Movements from Electroencephalogram Signals JH Kim, F Biessmann, SW Lee IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2014	110	2014
Temporal kernel CCA and its application in multimodal neuronal data analysis F Bießmann, FC Meinecke, A Gretton, A Rauch, G Rainer, NK Logothetis, ... Machine Learning 79 (1), 5-27, 2010	102	2010
Learning from more than one data source: data fusion techniques for sensorimotor rhythm-based brain–computer interfaces S Fazli, S Dähne, W Samek, F Bießmann, KR Müller Proceedings of the IEEE 103 (6), 891-906, 2015	96	2015
On Challenges in Machine Learning Model Management S Schelter, F Biessmann, T Januschowski, D Salinas, S Seufert, ... Bulletin of the IEEE Computer Society Technical Committee on Data …, 2018	93	2018
Multivariate machine learning methods for fusing multimodal functional neuroimaging data S Dähne, F Biessmann, W Samek, S Haufe, D Goltz, C Gundlach, ... Proceedings of the IEEE 103 (9), 1507-1530, 2015	86	2015
Quantifying Interpretability and Trust in Machine Learning Systems P Schmidt, F Biessmann AAAI-19 Workshop on Network Interpretability for Deep Learning, 2019	73	2019
Effects of stimulus type and of error-correcting code design on BCI speller performance J Hill, J Farquhar, S Martens, F Bießmann, B Schölkopf Advances in neural information processing systems 21, 2008	66	2008
Transparency and trust in artificial intelligence systems P Schmidt, F Biessmann, T Teubner Journal of Decision Systems 29 (4), 260-278, 2020	55	2020
Deep Learning for Missing Value Imputation in Tables with Non-Numerical Data F Biessmann, D Salinas, S Schelter, P Schmidt, D Lange Proceedings of the 27th ACM International Conference on Information and …, 2018	55	2018
DataWig: Missing Value Imputation for Tables. F Biessmann, T Rukat, P Schmidt, P Naidu, S Schelter, A Taptunov, ... J. Mach. Learn. Res. 20 (175), 1-6, 2019	48	2019
Regularized linear discriminant analysis of EEG features in dementia patients E Neto, F Biessmann, H Aurlien, H Nordby, T Eichele Frontiers in aging neuroscience 8, 273, 2016	47	2016
Stereoscopic depth increases intersubject correlations of brain networks M Gaebler, F Biessmann, JP Lamke, KR Mueller, H Walter, S Hetzer Neuroimage, 2014	44	2014
Simultaneous and proportional control of 2D wrist movements with myoelectric signals JM Hahne, H Rehbaum, F Biessmann, FC Meinecke, KR Müller, N Jiang, ... 2012 IEEE international workshop on machine learning for signal processing, 1-6, 2012	40	2012
Integration of multivariate data streams with bandpower signals S Dähne, F Biessmann, FC Meinecke, J Mehnert, S Fazli, KR Müller IEEE Transactions on Multimedia 15 (5), 1001-1013, 2013	34	2013
Functional and laminar dissociations between muscarinic and nicotinic cholinergic neuromodulation in the tree shrew primary visual cortex A Bhattacharyya, F Bießmann, J Veit, R Kretz, G Rainer European Journal of Neuroscience 35 (8), 1270-1280, 2012	23	2012
Learning to validate the predictions of black box classifiers on unseen data S Schelter, T Rukat, F Biessmann Proceedings of the 2020 ACM SIGMOD International Conference on Management of …, 2020	20	2020

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