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Maximising Sensitivity in a Spiking Network., and . NIPS, page 121-128. (2004)Hierarchical Image Probability (H1P) Models., and . NIPS, page 848-854. The MIT Press, (1999)Higher-Order Statistical Properties Arising from the Non-Stationarity of Natural Signals., , and . NIPS, page 786-792. MIT Press, (2000)Capturing contextual dependencies in medical imagery using hierarchical multi-scale models., , and . ISBI, page 165-168. IEEE, (2002)Correlated Components Analysis - Extracting Reliable Dimensions in Multivariate Data., , and . CoRR, (2018)Maximum Likelihood in Cost-Sensitive Learning: Model Specification, Approximations, and Upper Bounds., , and . J. Mach. Learn. Res., (2010)Nonnegative matrix factorization for rapid recovery of constituent spectra in magnetic resonance chemical shift imaging of the brain., , , , , , and . IEEE Trans. Med. Imaging, 23 (12): 1453-1465 (2004)Imaging artifacts induced by electrical stimulation during conventional fMRI of the brain., , , , , , and . NeuroImage, (2014)Unüberwachtes Lernen mit informationstheoretischen Kriterien in konnektionistischen Modellen.. Ludwig Maximilian University of Munich, Germany, (1995)Continuous Boltzmann machine with rotor neurons., and . Neural Networks, 8 (3): 375-385 (1995)