ScholarWorks@Korea University: Muller, Klaus Robert

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Muller, Klaus Robert (Klaus-Robert Muller)

Graduate School (Department of Artificial Intelligence)

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Tel 02-3290-5920
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EEG:14||machine learning:11||deep learning:8||Machine learning:7||Neural networks:7||fMRI:6||Deep learning:6||MEG:5||neural networks:5||Braincomputer interface (BCI):5||electroencephalography (EEG):4||nearinfrared spectroscopy (NIRS):4||structural support vector machines (SVMs):4||structured output:4||Feature extraction:4||Training:4||inference:4||braincomputer interfacing:4||Data models:3||Deep neural networks:3||classification:3||layerwise relevance propagation:3||Crossfrequency coupling:3||density functional theory:3||braincomputer interface:3||Supervised learning:3||Interpretability:3||Dynamic programming:3||motor imagery:3||highorder potentials:2||Subpopulation shift:2||common spatial patterns:2||multimodal:2||spatial filters:2||Graph neural networks:2||explainable artificial intelligence:2||Task analysis:2||Unsupervised learning:2||Multimodality:2||explaining classifiers:2||NIRS:2||Oscillations:2||Optimization:2||explainable machine learning:2||Artificial intelligence:2||BCI:2||Domain invariance:2||Wasserstein distance:2||fNIRS:2||nonstationarity:2||Braincomputer interfaces:2||data fusion:2||electromyography (EMG):2||Explainable AI:2||Servers:2||distributed learning:2||Electroencephalography (EEG):2||computer vision:2||robustness:2||dynamic programming:2||Motor imagery:2||graphical models:2||Afferent patterns:2||video quality assessment:2||Granger causality:2||Adaptation models:2||SPoC:2||Taylor series:2||Joint distribution matching:2||federated learning:2||Explainable machine learning:2||nearinfrared spectroscopy:2||MOS:2||Taylor decomposition:2||regression:2||hybrid BCI:2||electroencephalogram:2||simultaneous myoelectric control:2||Robustness:2||neuroimaging:2||connectivity:1||sensorimotor signals:1||prestimulus:1||Licenses:1||Switches:1||slack scaling:1||NID:1||Nonlinear neuronal interactions:1||Deep Taylor decomposition:1||Canonical correlation analysis:1||Entropy rate bound minimization:1||Machine learning force field:1||Ensemble learning:1||Multiclass classification:1||Quality of service:1||Interpretable learning:1||similarity preserving embeddings:1||covariance metrics:1||Genomics:1||Proteomics:1||Targeted cancer therapy:1||semisupervised and transductive learning:1||Activation maximization:1||multimodal biosignal acquisition architecture (M3BA):1||modular:1||linear models:1||Relevance propagation:1||time reversal:1||flicker:1||Regularization profile:1||artificial neural networks:1||Realtime systems:1||hyperparameters optimization:1||chemical compound space:1||Assistive technology:1||mutual information:1||somatosensory cortex:1||Canonical correlation analysis (CCA):1||image reconstruction:1||Multi task learning:1||PDC:1||PSI:1||Clever Hans predictors:1||Feature unlearning:1||Class Artifact Compensation:1||Adversarial attacks:1||neuromuscular electrical stimulation:1||Clustering:1||Ground truth:1||DNA methylation:1||deep neural networks:1||Image analysis:1||i:1||Cardiovascular risk factors:1||cerebrospinal fluid:1||Explainable AI (XAI):1||Counterfactual explanations:1||efficient communication:1||Inference algorithms:1||Blind source separation:1||Braincomputer interfacing (BCI) inefficiency:1||Image quality assessment:1||Visual perception:1||Path integral molecular dynamics:1||Coupled cluster calculations:1||Gradient domain machine learning:1||Stateless and stateful features:1||analyzing classifiers:1||stationary subspace analysis:1||spatiospectral decomposition:1||eventrelated potential (ERP):1||parameter estimation:1||explaining classification:1||stereoscopic images:1||Heaimapping:1||Image recognition:1||Contextfree grammar (CFG):1||probabilistic contextfree grammar (PCFG):1||BrainComputer Interfacing (BCI):1||implicit information:1||electromyogram (EMG):1||BCI inefficiency:1||performance increase:1||noise:1||Linear classifier:1||Systematic label noise:1||nonlinear gradient denoising:1||uniform selection:1||ASSEP:1||transfer learning:1||Image ranking:1||Multiple kernel learning:1||BagofWords representation:1||ImageCLEF:1||Mutual information:1||WMN:1||SFLEX:1||explainable artificial intelligence (XAI):1||motor disturbances:1||Sociology:1||machine learning applications:1||LSTM:1||Harmonic Minimization:1||digital humanities:1||open datasets:1||explainable AI:1||Model refinement:1||typeII maximumlikelihood:1||Biomarkers:1||XAI:1||kmeans clustering:1||"unsupervised learning:1||data manifold:1||muband:1||Bandpass filters:1||Nonlinear interaction decomposition:1||ICA:1||Physiological noise/nuisance regression:1||Functional nearinfrared spectroscopy:1||molecular simulation:1||Electromyography (EMG):1||Feature modeling:1||SVD:1||clustering:1||gazeindependent:1||noreference image quality assessment:1||feature extraction:1||image classification:1||interpretable machine learning:1||Porosity estimation:1||Latent variable:1||eventrelated potential:1||mental workload:1||Adaptation:1||online evaluation:1||Electromyography:1||vibrotactile stimulation:1||hierarchical tactile processing:1||brain imaging, simulation:1||unsupervised learning:1||Spectral Relevance Analysis:1||Manipulation:1||Statistics:1||Privacy:1||superresolution:1||molecular dynamics:1||molecular systems:1||brain computer interface (BCI):1||brain plasticity:1||Brainage:1||algorithm:1||optimization:1||Condition monitoring:1||EEG/MEG brain source imaging:1||Explainable artificial intelligence:1||Molecular biology:1||BCI efficiency:1||image regression:1||privacypreserving machine learning:1||Grammar:1||Computational modeling:1||margin scaling:1||Independent component analysis:1||brainswitch:1||Multivariate methods:1||Artifact removal:1||Machine learning potential:1||Quantum chemistry:1||Mobile communication:1||optimal transport:1||oneclass classification:1||Layerwise relevance propagation:1||margin scaling (MS):1||Ridge regression:1||quality of experience:1||objective assessment:1||natural language parsing:1||pattern recognition:1||brain computer interfaces:1||Pattern classification:1||extreme behaviors:1||molecular properties:1||communication:1||hybrid braincomputer interface (hBCI):1||Intersubject correlations:1||Natural viewing:1||3D movies:1||prosthetic hand:1||ECoG:1||gene finding:1||slack rescaling:1||information geometry:1||Inverse source reconstruction:1||Blackbox models:1||Deep Neural Networks:1||Saliency map:1||multitask learning:1||quality assurance methodology:1||guidelines:1||trajectory learning:1||Spurious interactions:1||Benchmark:1||Linear classification:1||cancer of unknown primary:1||braincomputer interface (BCI):1||Pathology:1||Explainable a:1||majorization minimization:1||sparse Bayesian learning:1||Brain:1||electroencephalography:1||Temporal embedding:1||coarse graining:1||decoding:1||wholebrain:1||Multimodal methods:1||Motor imagery (MI):1||stimulation (STM):1||Structured data:1||Artificial neural networks:1||divergence methods:1||kmeans:1||Conditional random fields (CRFs):1||information transfer rate:1||rapid serial visual presentation (RSVP):1||P300 speller:1||mobile:1||Multiclass Classification:1||Braincomputer interfacing:1||online learning:1||reproducing kernel Hilbert space (RKHS):1||selfconsistent calculation:1||TRGC:1||3D shutter glasses:1||ERP:1||multimodal neuroimaging:1||neuroprosthesis:1||diffuse optical tomography:1||LFP:1||cSPoC:1||subjecttosubject transfer:1||P300:1||label sequence learning:1||Source power comodulation:1||Efferent pattern classification:1||BCIinefficency:1||Biased random sampling:1||GC:1||LCMV:1||bidirectional recurrent neural networks:1||Suppressor variables:1||head and neck squamous cell carcinoma:1||Molecular pathology:1||cell detection:1||Clever Hans effect:1||Catalyst degradation:1||BCI performance:1||onset detection:1||Protocols:1||Training data:1||Outlier detection:1||Computationally efficient deep learning:1||sparse matrices:1||General linear model:1||Corticomuscular coherence (CMC):1||Magnetoencephalography (MEG):1||Local field potentials (LFP):1||matrix factorization:1||Pancancer analysis:1||support vector data description (SVDD):1||nonindependent and identically distributed (IID):1||slack scaling (SS):1||relevance models:1||EEG analysis:1||mathematical models:1||theoretical models:1||Multilabel Classification:1||Classifier Chain:1||independent component analysis:1||neurotechnology:1||Searchlight:1||Singletrial classification:1||review:1||multimodal:1||hand prostheses:1||model transparency:1||induced movements:1||afferent signals:1||process model:1||automotive industry and academia:1||Langevin dynamics:1||Saliency methods:1||Similarity:1||neural decoding:1||Pruning:1||Wind turbine power curve:1||hierarchical Bayesian learning:1||Speech recognition:1||pathology:1||Predictive maintenance:1||mammography image quality assessment:1||Electroencephalography:1||Loss measurement:1||lossless coding:1||quantum mechanics:1||kinetics:1||High density electromyography (HDsEMG):1||Neuroimaging in motion:1||Sensory threshold neuromuscular electrical:1||Efferent patterns:1||Perceptual coding:1||Ab initio molecular dynamics:1||kernel PCA:1||Cancer:1||Fullreference image quality assessment:1||Convolutional neural networks:1||mental arithmetic:1||open access dataset:1||Facies classification:1||Conditional random fields:1||vertical disparity:1||wireless body area network (WBAN):1||wireless body sensor network (WBSN):1||margin rescaling (MR):1||covert user states:1||cognitive neuroscience:1||Brain computer interfacing:1||Neuralprosthesis:1||myoelectric signals:1||nonstationarities:1||orbital free:1||kinetic energy functional:1||Subclass:1||Calibration:1||atomization energies:1||SSVEPs:1||functional specialization:1||Immersion:1||sequential feature selection (SFS):1||Powertopower coupling:1||visual eventrelated potentials:1||speller matrix:1||margin rescaling:1||Neuromuscular electrical stimulation:1||common spatial patterns (CSP):1||Explanation method:1||best practices:1||Predictive models:1||functional connectivity:1||Structural mri:1||Audio classification:1||generative models:1||Time series prediction:1||brain switch:1||Distributed databases:1||Kernel machines:1||data structures:1||neural network compression:1||recurrent:1||interpretability:1||Coherence optimization:1||Distortion sensitivity:1||Molecular property prediction:1||Nary ECOC:1||dimensionality reduction:1||Subspace learning:1||Anomaly detection:1||SSVEP:1||ridge regression (RR):1||pseudoonline:1||Sensitivity analysis:1||quality pooling:1||hybrid braincomputer interface (BCI):1||coadaptation:1||slack rescaling (SR):1||Easytohard Learning Paradigm:1||video quality:1||Functional electrical stimulation:1||Kernel adaptive filter:1||covariate shift:1||singletrial classification:1||Shrinkage:1||Datadriven clustering:1||Electrodes:1||noisefree curve:1||orbitalfree density functional theory:1||manybody potentials:1||zerotraining:1||channel selection:1||least absolute shrinkage and selection operator (LASSO):1||inverse problem:1||Neural oscillations:1||hidden Markov SVM:1||Amputee:1||EEGNIRS:1||Image classification:1||Effective connectivity:1||Explainable Artificial Intelligence:1||feedback contingency:1||Adversarial examples:1||Nonsinusoidal oscillations:1||competition:1||higherorder explanations:1||Ageing:1||heatmaps:1||SCADA:1||Wind energy:1||Precision medicine:1||"neuralization:1||

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