FG Maschinelles Lernen

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PreviewIssue DateTitleAuthor(s)Editor(s)
make-03-00020-v3.pdf.jpg22-Apr-2021Towards CRISP-ML(Q): A Machine Learning Process Model with Quality Assurance MethodologyStuder, Stefan; Bui, Thanh Binh; Drescher, Christian; Hanuschkin, Alexander; Winkler, Ludwig; Peters, Steven; Müller, Klaus-Robert-
liu_yang.pdf.jpg2021Identification of nodes and NetworksLiu, Yang-
Sauceda_etal_Dynamical_2020.pdf.jpg19-Jan-2021Dynamical strengthening of covalent and non-covalent molecular interactions by nuclear quantum effects at finite temperatureSauceda, Huziel E.; Vassilev-Galindo, Valentin; Chmiela, Stefan; Müller, Klaus-Robert; Tkatchenko, Alexandre-
Vidaurre_etal_Sensorimotor_2020.pdf.jpg18-Dec-2020Sensorimotor functional connectivity: A neurophysiological factor related to BCI performanceVidaurre, Carmen; Haufe, Stefan; Jorajuría, Tania; Müller, Klaus-Robert; Nikulin, Vadim V.-
thomas_armin.pdf.jpg2020Machine learning methods for modeling gaze allocation in simple choice behavior and functional neuroimaging data on the level of the individualThomas, Armin W.-
Letzgus_Change-point_2020.pdf.jpg27-Oct-2020Change-point detection in wind turbine SCADA data for robust condition monitoring with normal behaviour modelsLetzgus, Simon-
journal.pone.0174392.pdf.jpg27-Mar-2017ML2Motif—Reliable extraction of discriminative sequence motifs from learning machinesVidovic, Marina Marie-Claire; Kloft, Marius; Müller, Klaus-Robert; Görnitz, Nico-
journal.pone.0172578.pdf.jpg22-Feb-2017A convolutional neural network for steady state visual evoked potential classification under ambulatory environmentKwak, No-Sang; Müller, Klaus-Robert; Lee, Seong-Whan-
24-Sep-2020Molecular force fields with gradient-domain machine learning (GDML): Comparison and synergies with classical force fieldsSauceda, Huziel E.; Gastegger, Michael; Chmiela, Stefan; Müller, Klaus-Robert; Tkatchenko, Alexandre-
fninf-14-573750.pdf.jpg26-Oct-2020Beyond Pairwise Interactions: The Totally Antisymmetric Part of the Bispectrum as Coupling Measure of at Least Three Interacting SourcesBartz, Sarah; Andreou, Christina; Nolte, Guido-
TJP_TJP13838.pdf.jpg6-Nov-2019Immediate brain plasticity after one hour of brain–computer interface (BCI)Nierhaus, Till; Vidaurre, Carmen; Sannelli, Claudia; Müller, Klaus-Robert; Villringer, Arno-
kretz_tobias.pdf.jpg2020Development of model observers for quantitative assessment of mammography image qualityKretz, Tobias-
Gastegger_etal_2019.pdf.jpg14-Dec-2018Exploring density functional subspaces with genetic algorithmsGastegger, Michael; González, Leticia; Marquetand, Philipp-
acs.jpclett.0c00527.pdf.jpg20-Apr-2020Combining SchNet and SHARC: The SchNarc Machine Learning Approach for Excited-State DynamicsWestermayr, Julia; Gastegger, Michael; Marquetand, Philipp-
c9sc01742a.pdf.jpg5-Aug-2019Machine learning enables long time scale molecular photodynamics simulationsWestermayr, Julia; Gastegger, Michael; Menger, Maximilian F. S. J.; Mai, Sebastian; González, Leticia; Marquetand, Philipp-
brandl_lassner_2019.pdf.jpg2-Aug-2019Times Are Changing: Investigating the Pace of Language Change in Diachronic Word EmbeddingsBrandl, Stephanie; Lassner, David-
schuett_etal_2019.pdf.jpg10-Sep-2019Quantum-Chemical Insights from Interpretable Atomistic Neural NetworksSchütt, Kristof T.; Gastegger, Michael; Tkatchenko, Alexandre; Müller, Klaus-Robert-
gastegger_marquetand_2020.pdf.jpg4-Jun-2020Molecular Dynamics with Neural Network PotentialsGastegger, Michael; Marquetand, Philipp-
horn_franziska.pdf.jpg2020Similarity encoder: A neural network architecture for learning similarity preserving embeddingsHorn, Franziska-
electronics-09-00422.pdf.jpg2-Mar-2020Brain-Switches for Asynchronous Brain−Computer Interfaces: A Systematic ReviewHan, Chang-Hee; Müller, Klaus-Robert; Hwang, Han-Jeong-
Collection's Items (Sorted by Submit Date in Descending order): 1 to 20 of 55