 | Up a level |
Urbanczik, R; Senn, W (2009). A gradient learning rule for the tempotron. Neural computation, 21(2), pp. 340-352. Cambridge, Mass.: MIT Press 10.1162/neco.2008.09-07-605
Urbanczik, R; Senn, W (2009). Reinforcement learning in populations of spiking neurons. Nature neuroscience, 12(3), pp. 250-252. New York, N.Y.: Nature America 10.1038/nn.2264
Vasilaki, E; Frémaux, N; Urbanczik, R; Senn, W; Gerstner, W (2009). Spike-Based Reinforcement Learning in Continuous State and Action Space: When Policy Gradient Methods Fail. PLoS computational biology, 5(12), e1000586. San Francisco, Calif.: Public Library of Science 10.1371/journal.pcbi.1000586
Urbanczik, R (2007). Enumerating constrained elementary flux vectors of metabolic networks. IET systems biology, 1(5), pp. 274-9. Stevenage, UK: IET 10.1049/iet-syb:20060073
Vladimirskiy, BB; Vasilaki, E; Urbanczik, R; Senn, W (2009). Stimulus sampling as an exploration mechanism for fast reinforcement learning. In: Biol. Cybern 100 100 (pp. 319-330). Springer-Verlag 10.1007/s00422-009-0305-x
