FG Maschinelles Lernen

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PreviewIssue DateTitleAuthor(s)Editor(s)
9-Jul-2016Multiscale temporal neural dynamics predict performance in a complex sensorimotor taskSamek, Wojciech; Blythe, Duncan A. J.; Curio, Gabriel; Klaus-Robert, Müller; Blankertz, Benjamin; Nikulin, Vadim V.-
5-Jun-2018Improvement of Information Transfer Rates Using a Hybrid EEG-NIRS Brain-Computer Interface with a Short Trial Length: Offline and Pseudo-Online AnalysesShin, Jaeyoung; Kim, Do-Won; Müller, Klaus-Robert; Hwang, Han-Jeong-
alber_maximilian.pdf.jpg2019Efficient learning machinesAlber, Maximilian-
29-Aug-2018On the Feasibility of Using an Ear-EEG to Develop an Endogenous Brain-Computer InterfaceChoi, Soo-In; Han, Chang-Hee; Choi, Ga-Young; Shin, Jaeyoung; Song, Kwang Soup; Im, Chang-Hwan; Hwang, Han-Jeong-
2019Towards exact molecular dynamics simulations with invariant machine-learned modelsChmiela, Stefan-
schwenk_guido.pdf.jpg2019Features and machine learning systems for structured and sequential dataSchwenk, Guido-
2019One-class classification in the presence of point, collective, and contextual anomaliesGörnitz, Nico-
lapuschkin_sebastian.pdf.jpg2019Opening the machine learning black box with Layer-wise Relevance PropagationLapuschkin, Sebastian-
10.1515.PIKO.2004.228.pdf.jpg2004Intrusion Detection in Unlabeled Data with Quarter-sphere Support Vector MachinesLaskov, Pavel; Schäfer, Christin; Kotenko, Igor; Müller, Klaus-Robert-
2018Multimodal instrumentation and methods for neurotechnology out of the labLühmann, Alexander von-
2018Functional regression of densities with application to the simulation of molecular dynamicsBrockherde, Felix-
shelton_jacquelyn-ann.pdf.jpg2018Large-scale approximate EM-style learning and inference in generative graphical models for sparse codingShelton, Jacquelyn Ann-
schuett_kristof.pdf.jpg2018Learning representations of atomistic systems with deep neural networksSchütt, Kristof-
May-2017Explaining nonlinear classification decisions with deep Taylor decompositionMontavon, Grégoire; Lapuschkin, Sebastian; Binder, Alexander; Samek, Wojciech; Müller, Klaus-Robert-
e1603015.full.pdf.jpg2017Machine learning of accurate energy-conserving molecular force fieldsChmiela, Stefan; Tkatchenko, Alexandre; Sauceda, Huziel E.; Poltavsky, Igor; Schütt, Kristof T.; Müller, Klaus-Robert-
2017_hwang_et-al.pdf.jpg2017Real-time robustness evaluation of regression based myoelectric control against arm position change and donning/doffingHwang, Han-Jeong; Hahne, Janne Mathias; Müller, Klaus-Robert-
2017_kindermans_et-al.pdf.jpg2017Learning from label proportions in brain-computer interfacesHübner, David; Verhoeven, Thibault; Schmid, Konstantin; Müller, Klaus-Robert; Tangermann, Michael; Kindermans, Pieter-Jan-
bauer_alexander.pdf.jpg2017Universal exact algorithm for globally augmented MAP inference in structured predictionBauer, Alexander-
bmt-2013-4439.pdf.jpg2013Zero training for BCI – Reality for BCI systems based on event-related potentialsTangermann, Michael; Kindermans, Pieter-Jan; Schreuder, Martijn; Schrauwen, Benjamin; Müller, Klaus-Robert-
bmt-2013-4435.pdf.jpg2013The hybrid brain-computer interface: a bridge to assistive technology?Müller-Putz, Gernot R.; Schreuder, Martijn; Tangermann, Michael; Leeb, R.; Millán del, R. J.-
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