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Inhalt des Dokuments

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Graepel, T., Herbrich, R. and Obermayer, K. (2000). Bayesian Transduction. Advances in Neural Information Processing Systems 12. MIT Press, 456 – 462.,


Graepel, T., Herbrich, R. and Obermayer, K. (1999). Bayesian transductive classification by maximizing volume in version space. Proceedings of Learning 1999 Conference,


Graepel, T., Herbrich, R., Schoelkopf, B., Smola, A., Bartlett, P., Mueller, K., Obermayer, K. and Williamson, R. (1999). Classification on Proximity Data with LP-Machines. 9th International Conference on Artificial Neural Networks - ICANN99. IEEE, 304 – 309.,10.1049/cp:19991126


Graepel, T. and Obermayer, K. (1998). Fuzzy Topographic Kernel Clustering. Proceedings of the 5th GI Workshop Fuzzy Neuro Systems, 90 – 97.,


Graepel, T. and Obermayer, K. (1999). A Self-Organizing Map for Proximity Data. Neural Computation, 11, 139 – 155.


Goerttler, T., Müller, L. and Obermayer, K. (2022). Representation Change in Model-Agnostic Meta-Learning. ICLR Blog Track


Goerttler, T. and Obermayer, K. (2021). Exploring the Similarity of Representations in Model-Agnostic Meta-Learning. Learning to Learn workshop at ICLR 2021


Gaudnek, M., Hess, A., Obermayer, K., Budinsky, L., Brune, K. and Sibila, M. (2005). Geometric Reconstruction of the Rat Vascular System Imaged by MRA. IEEE International Conference on Image Processing 2005. IEEE, 1278-1281.,10.1109/ICIP.2005.1530296


Garg, A., Bhaumik, B. and Obermayer, K. (2005). Variable Discharge Pattern and Contrast Invariant Orientation Tuning of a Simple Cell: A Modeling Study. Neural Information Processing - Letters and Reviews, 6, 59 – 68.



Garg, A., Bhaumik, B. and Obermayer, K. (2004). Development of a Simple Cell Preceptive Field Structure: A Model Based on Hetero-Synaptic Interactions. Lecture Notes in Computer Science. Springer-Verlag, 64 – 68.,


Garg, A., Obermayer, K. and Bhaumik, B. (2005). Development of Feedforward Receptive Field Structure of a Simple Cell and its Contribution to the Orientation Selectivity: A Modeling Study. International Journal of Neural Systems, 15, 55 – 70.


Gallinat, J., Obermayer, K. and Heinz, A. (2007). Systems Biology of the Dysfunctional Brain: Schizophrenia. Pharmacopsychiatry, 40, 40 – 44.


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Franke, F., Natora, M., Boucsein, C., Munk, M. and Obermayer, K. (2010). An Online Spike Detection and Spike Classification Algorithm Capable of Instantaneous Resolution of Overlapping Spikes. Journal of Computional Neuroscience, 127 – 148.


Franke, F., Natora, M., Meier, P., Hagen, E., Pettersen, K., Linden, H., Einevoll, G. and Obermayer, K. (2010). An Automated Online Positioning System and Simulation Environment for Multi-Electrodes in Extracellular Recordings. Proceedings of 32nd Annual International Conference of the IEEE EMBS, 593 – 597.,10.1109/IEMBS.2010.5626631


Franke, F., Natora, M., Munk, M. and Obermayer, K. (2009). Blind Source Separation of Sparse Overcomplete Mixtures and Application to Neural Recordings. Independent Component Analysis and Signal Separation. Springer Berlin Heidelberg, 459 – 466.,10.1007/978-3-642-00599-2_58


Franke, F., Pröpper, R., Alle, H., Meier, P., Geiger, J. R. P., Obermayer, K. and Munk, M. H. J. (2015). Spike sorting of synchronous spikes from local neuron ensembles. Journal of Neurophysiology, 114, 2535–2549.


Franke, F., Quiroga, R. Q., Hierlemann, A. and Obermayer, K. (2015). Bayes optimal template matching for spike sorting – combining fisher discriminant analysis with optimal filtering. Journal of Computational Neuroscience, 38, 439-459.


E

Erwin, E., Obermayer, K. and Schulten, K. (1993). A Comparison of Models of Visual Cortical Map Formation. Computation and Neural Systems. Kluwer Academic Publishers, 395 – 402.,10.1.1.51.910


Erwin, E., Obermayer, K. and Schulten, K. (1991). Convergence Properties of Self-organizing Maps. Artificial Neural Networks I. North Holland, 409 – 414.,


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