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Schönfelder, V.H. and Wichmann, F.A. (2010). Machine Learning in Auditory Psychophysics: System Identification with Sparse Pattern Classifiers [23]. Proceedings of KogWis – 10th Meeting of the German Society for Cognitive Science, Potsdam, 2010


Schleimer, J.-H., and Stemmler, M. (2009). Neuronal Phase Response Curves for Maximal Information Transmission [24]. Bernstein Conference on Computational Neuroscience in Frankfurt


Samek, W., Kawanabe, M., and Vidaurre, C. (2011). Group-wise Stationary Subspace Analysis - A Novel Method for Studying Non-Stationarities [25]. Proceedings of 5th International Brain-Computer Interface Conference 2011


Roemschied, F.A., Eberhard, M.J.B., Ronacher, B., and Schreiber, S. (2011). Single-neuron Mechanisms of Temperature Compensation in the Locust Auditory System. Conference abstract and poster presentation [26]. Champalimaud Neuroscience Symposium, Lisbon, Portugal


Onken, A., Grünewälder, S., Munk, M. H. J., and Obermayer, K. (2010). A Maximum Entropy Mutual Information Test for Spike Counts of V1. [27]. Society for Neuroscience Annual Meeting 2010, San Diego, California.


Onken, A. (2011). Stochastic Analysis of Neural Spike Count Dependencies [28]. Technische Universität Berlin


Natora, M., Franke, F., Boucsein, C., Munk, M.H., and Obermayer, K. (2008). Online Spike Sorting with Optimal Multichannel Filters [29]. 4th International Workshop on Statistical Analysis of Neuronal Data (SAND4), Pittsburgh PA, USA


Natora, M., Franke, F., and Obermayer, K. (2010). Spike Detection in Extracellular Recordings by Hybrid Blind Beamforming [30]. 32nd Annual International IEEE EMBS Conference 2010, Buenos Aires, Argentina


Natora, M., Franke, F., and Obermayer, K. (2009). Optimal Convolutive Filters for Real-Time Detection and Arrival Time Estimation of Transient Signals [31]. World Academy of Science, Engineering and Technology 55, Oslo, Norway


Kawanabe, M., Samek, W., von Bünau, P., and Meinecke, F. (2011). An information geometrical view of stationary subspace analysis [32]. Artificial Neural Networks and Machine Learning – ICANN 2011. Springer Berlin / Heidelberg, 397-404.


Häusler, C., Nawrot, M. P., and Schmuker, M. (2011). A spiking neuron classifier network with a deep architecture inspired by the olfactory system of the honeybee [33]. 5th International IEEE EMBS Conference on Neural Engineering 2011, Cancun, Mexico


Hackmack, K. (2009). Decoding Multiple Sclerosis from MRI Brain Patterns [34]. Berln Brain Days


Hackmack, K. (2010). Predicting Clinical Disability in Multiple Sclerosis Based on Structural MRI [35]. International Conference on Neuroimmunology


Hackmack, K. (2010). Decoding Symptom Severity in Multiple Sclerosis Using Structural MRI Brain Patterns [36]. Human Brain Mapping


Görgen, K., Reverberi, C., and Haynes, J.-D. (2010). Decoding neural representations of rules and rule order [37]. Poster Abstract, Bernstein Conference on Computational Neuroscience. Berlin, Germany, 27 Sep - 1 Oct, 2010. In FRONTIERS EVENTS: Bernstein Conference on Computational Neuroscience.


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