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Jens Kohlmorgen

Observed names: J. Kohlmorgen, JENS KOHLMORGEN, Kohlmorgen, J., Kohlmorgen, Jens
OpenAlex ID: A5036784111
Predicting time series with support vector machines
1997 · K. -R. Müller, A. J. Smola, et al. · Lecture notes in computer science · 998
Boosting bit rates and error detection for the classification of fast-paced motor commands based on single-trial EEG analysis
2003 · B. Blankertz, G. Dornhege, et al. · IEEE Transactions on Neural Systems and Rehabilitation Engineering · 225
Improving Human Performance in a Real Operating Environment through Real-Time Mental Workload Detection
2007 · Jens Kohlmorgen, Guido Dornhege, et al. · The MIT Press eBooks · 183
Using support vector machines for time series prediction
1999 · Klaus‐Robert Müller, Alexander J. Smola, et al. · 144
Annealed Competition of Experts for a Segmentation and Classification of Switching Dynamics
1996 · Klaus Pawelzik, Jens Kohlmorgen, et al. · Neural Computation · 93
Using Support Vector Machines for Time Series Prediction
1998 · Klaus-Robert Müller, Alex J. Smola, et al. · The MIT Press eBooks · 77
A Dynamic HMM for On-line Segmentation of Sequential Data
2001 · Jens Kohlmorgen, Steven Lemm · 69
Identification of nonstationary dynamics in physiological recordings
2000 · J. Kohlmorgen, K.-R. M�ller, et al. · Biological Cybernetics · 50
Analysis of switching dynamics with competing neural networks
1995 · K. Müller, Jens Kohlmorgen, et al. · 34
An on-line method for segmentation and identification of non-stationary time series
2002 · J. Kohlmorgen, S. Lemm · Machine learning for signal processing ... · 19
Hidden Markov mixtures of experts with an application to EEG recordings from sleep
1999 · Stefan Liehr, Klaus Pawelzik, et al. · 19
Segmentation and identification of drifting dynamical systems
2002 · J. Kohlmorgen, K.-R. Muller, et al. · Machine learning for signal processing ... · 12
Hidden Markov mixtures of experts for prediction of non-stationary dynamics
2003 · S. Liehr, K. Pawelzik, et al. · Machine learning for signal processing ... · 10
A Dynamic HMM for Online Segmentation of Sequential Data
2002 · Jens Kohlmorgen, Steven Lemm · The MIT Press eBooks · 9
Fast change point detection in switching dynamics using a hidden Markov model of prediction experts
1999 · J. Kohlmorgen · International Conference on Artificial Neural Networks · 9
Analysis of Drifting Dynamics with Neural Network Hidden Markov Models
1997 · Jens Kohlmorgen, Klaus‐Robert Müller, et al. · 8
Bayesian Classification of Single-trial Event-related Potentials in Eeg
2004 · JENS KOHLMORGEN, BENJAMIN BLANKERTZ · International Journal of Bifurcation and Chaos · 7
On optimal segmentation of sequential data
2003 · J. Kohlmorgen · Machine learning for signal processing ... · 6
Analysis of nonstationary time series by mixtures of self-organizing predictors
2002 · J. Kohlmorgen, S. Lemm, et al. · Machine learning for signal processing ... · 6
Decomposition algorithms for analysing brain signals
2002 · K.-R. Muller, J. Kohlmorgen, et al. · IEEE Adaptive Systems for Signal Processing, Communications, and Control Symposium (AS-SPCC) · 4
A Simple Generative Model for Single-Trial EEG Classification
2002 · Jens Kohlmorgen, Benjamin Blankertz · Lecture notes in computer science · 4
Data Set A is a Pattern Matching Problem
1998 · Jens Kohlmorgen, Klaus-Robert Müller · Neural Processing Letters · 4
Prediction of mixtures
1996 · K. Pawelzik, K. -R. Müller, et al. · Lecture notes in computer science · 4
Hidden Markov gating for prediction of change points in switching dynamical systems.
1999 · Stefan Liehr, Klaus Pawelzik, et al. · 3
Analysis of wake/sleep EEG with competing experts
1997 · J. Kohlmorgen, K. -R. Müller, et al. · Lecture notes in computer science · 3
Works count: 50
Citation count: 2,024
H-index: 12
I10-index: 14
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