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Xie, S., Zhu, F., Obermayer, K., Ritter, P. and Wang, L. (2013). An Efficient Spatial Selective Visual Attention Pattern Recognition Method Based on Joint Short SSVEP. ,10.1109/IJCNN.2013.6706872


Erdi, P., Kepecs, A., Lengyel, M., Obermayer, K. and Szatmary, Z. (1998). Dynamics of the hippocampus: multiple strategies. Proceedings of the ICONIP 98 Conference, Kitakyushu, 777 – 780.,10.1.1.45.4878


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.,


Erwin, E., Obermayer, K. and Schulten, K. (1992). Formation and Variability of Somatotopic Maps with Topological Mismatch. Proceedings of the 4th International Conference on Neural Networks, 115 – 126.,


Erwin, E., Obermayer, K. and Schulten, K. (1995). A Critical Comparison of Models for Orientation and Ocular Dominance Columns in the Striate Cortex. Advances in Neural Information Processing Systems 7. MIT Press, 93 – 100.,


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


Kim, H., Obermayer, K., Bode, M. and Ruwisch, D. (2001). Modified Spectral Substraction using Diffusive Gain Factors. Proceedings IEEE/EURASIP International Workshop on Acoustic Echo and Noise Control,



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.,


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


Grünewälder, S. and Obermayer, K. (2007). Optimality of LSTD and its Relation to MC. Neural Networks, IJCNN 2007, 338 – 343.,


Grünewälder, S. and Obermayer, K. (2005). Attention Driven Memory. Proceedings of the 27th Annual Conf. of the Cognitive Science Society, 845 – 850.,


Graepel, T., Burger, M. and Obermayer, K. (1997). Deterministic Annealing for Topographic Vector Quantization and Self-Organizing Maps. Proceedings of the Workshop on Self-Organizing Maps - WSOM 97, 345 – 350.,


Graepel, T., Herbrich, R., Bollmann-Sdorra, P. and Obermayer, K. (1999). Classification on Pairwise Proximity Data. Advances in Neural Information Processing Systems 11. MIT Press, 438 – 444.,


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


Hasenjäger, M., Ritter, H. and Obermayer, K. (1999). Active Data Selection for Fuzzy Topographic Mapping of Proximities. Fuzzy-Neuro Systems 1999 - Computational Intelligence, 93–104.,


Hasenjäger, M., Ritter, H. and Obermayer, K. (2000). Active Data Selection for Topographic Pairwise Clustering. Classification, Automation, and New Media. Program of the 24th Annual Conference of the German Classification Society (GfKl), 80.,


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