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STDP in Adaptive Neurons Gives Close-To-Optimal Information Transmission.

, , and . Frontiers Comput. Neurosci., (2010)

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Asymptotically Exact Unweighted Particle Filter for Manifold-Valued Hidden States and Point Process Observations., , and . IEEE Control. Syst. Lett., 4 (2): 480-485 (2020)Rate-Distortion Problems of the Poisson Process: a Group-Theoretic Approach., , and . ITW, page 1-6. IEEE, (2021)Bayesian regression explains how human participants handle parameter uncertainty., , , , and . PLoS Comput. Biol., (2020)Sequence learning with hidden units in spiking neural networks., , and . NIPS, page 1422-1430. (2011)How to Avoid the Curse of Dimensionality: Scalability of Particle Filters with and without Importance Weights., , and . SIAM Rev., 61 (1): 79-91 (2019)Matching Recall and Storage in Sequence Learning with Spiking Neural Networks, , and . The Journal of Neuroscience, 33 (23): 9565--9575 (2013)Reinforcement Learning in Cortical Networks., and . Encyclopedia of Computational Neuroscience, Springer, (2014)A Unification of Weighted and Unweighted Particle Filters., , and . CoRR, (2020)Online Maximum-Likelihood Estimation of the Parameters of Partially Observed Diffusion Processes., and . IEEE Trans. Automat. Contr., 64 (7): 2814-2829 (2019)Sphere Covering for Poisson Processes., , and . ITW, page 1-5. IEEE, (2020)