Suchergebnisse

Zeitschriftenartikel (233)

221.
Zeitschriftenartikel
Dayan, P.; Hinton, G.; Neal, R.; Zemel, R.: The Helmholtz Machine. Neural computation 7 (5), S. 889 - 904 (1995)
222.
Zeitschriftenartikel
Dayan, P.; Zemel, R.: Competition and Multiple Cause Models. Neural computation 7 (3), S. 565 - 579 (1995)
223.
Zeitschriftenartikel
Hinton, G.; Dayan, P.; Frey, B.; Neal, R.: The "wake-sleep" algorithm for unsupervised neural networks. Science 268 (5214), S. 1158 - 1161 (1995)
224.
Zeitschriftenartikel
Dayan, P.: Computational Modelling. Current Opinion in Neurobiology 4 (2), S. 212 - 217 (1994)
225.
Zeitschriftenartikel
Dayan, P.; Sejnowski, T.: TD(λ) converges with probability 1. Machine Learning 14 (3), S. 295 - 301 (1994)
226.
Zeitschriftenartikel
Berns, G.; Dayan, P.; Sejnowski, T.: A correlational model for the development of disparity selectivity in visual cortex that depends on prenatal and postnatal phases. Proceedings of the National Academy of Sciences of the United States of America 90 (17), S. 8277 - 8281 (1993)
227.
Zeitschriftenartikel
Dayan, P.: Improving Generalization for Temporal Difference Learning: The Successor Representation. Neural computation 5 (4), S. 613 - 624 (1993)
228.
Zeitschriftenartikel
Dayan, P.: Arbitrary Elastic Topologies and Ocular Dominance. Neural computation 5 (3), S. 392 - 401 (1993)
229.
Zeitschriftenartikel
Dayan, P.; Sejnowski, T.: The Variance of Covariance Rules for Associative Matrix Memories and Reinforcement Learning. Neural computation 5 (2), S. 205 - 209 (1993)
230.
Zeitschriftenartikel
Dayan, P.: The Convergence of TD(λ) for General λ. Machine Learning 8 (3-4), S. 341 - 362 (1992)
231.
Zeitschriftenartikel
Watkins, C.; Dayan, P.: Q-learning. Machine Learning 8 (3-4), S. 279 - 292 (1992)
232.
Zeitschriftenartikel
Dayan, P.; Willshaw, D.: Optimising synaptic learning rules in linear associative memories. Biological Cybernetics 65 (4), S. 253 - 265 (1991)
233.
Zeitschriftenartikel
Willshaw, D.; Dayan, P.: Optimal Plasticity from Matrix Memories: What Goes Up Must Come Down. Neural computation 2 (1), S. 85 - 93 (1990)

Buch (1)

234.
Buch
Dayan, P.; Abbott, L.: Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems. MIT Press, Cambridge, MA, USA (2001), 460 S.

Buchkapitel (4)

235.
Buchkapitel
Dayan, P.; Nakahara, H.: Models and Methods for Reinforcement Learning. In: Stevens' Handbook of Experimental Psychology and Cognitive Neuroscience, Bd. 5: Methodology, 4. Aufl., S. 1 - 40 (Hg. Wixted, J.; Wagenmakers, E.-J.). Wiley, Hoboken, NJ, USA (2018)
236.
Buchkapitel
Dayan, P.: Exploration from Generalization Mediated by Multiple Controllers. In: Intrinsically Motivated Learning in Natural and Artificial Systems, S. 73 - 91 (Hg. Baldassarre, G.; Mirolli, M.). Springer, Berlin, Germany (2013)
237.
Buchkapitel
Dayan, P.: Models of Value and Choice. In: Neuroscience of Preference and Choice: Cognitive and Neural Mechanisms, 2, S. 33 - 52 (Hg. Dolan, R.; Sharot, T.). Elsevier/Academic Press, London, UK (2012)
238.
Buchkapitel
Platt, M.; Dayan, P.; Dehaene, S.; McCabe, H.; Menzel, R.; Phelps, E.; Plassmann, H.; Ratcliff, R.; Shadlen, M.; Singer, W.: Neuronal Correlates of Decision Making. In: Better than conscious?: decision making, the human mind, and implications for institutions, 6 (Hg. Engel, C.; Singer, W.). MIT Press, Cambridge, MA, USA (2008)

Konferenzband (1)

239.
Konferenzband
Exploration and Curiosity in Robot Learning and Inference (Dagstuhl Reports, 1). Dagstuhl Seminar 11131, Dagstuhl, Germany, 27. März 2011 - 01. April 2011. (2011)

Konferenzbeitrag (69)

240.
Konferenzbeitrag
Tano, P.; Dayan, P.; Pouget, A.: A local temporal difference code for distributional reinforcement learning. In: Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS 2020). Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS 2020), 07. Dezember 2020 - 12. Dezember 2020. (angenommen)
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