Search results

Journal Article (227)

  1. 221.
    Journal Article
    Dayan, P.: Improving Generalization for Temporal Difference Learning: The Successor Representation. Neural computation 5 (4), pp. 613 - 624 (1993)
  2. 222.
    Journal Article
    Dayan, P.: Arbitrary Elastic Topologies and Ocular Dominance. Neural computation 5 (3), pp. 392 - 401 (1993)
  3. 223.
    Journal Article
    Dayan, P.; Sejnowski, T.: The Variance of Covariance Rules for Associative Matrix Memories and Reinforcement Learning. Neural computation 5 (2), pp. 205 - 209 (1993)
  4. 224.
    Journal Article
    Dayan, P.: The Convergence of TD(λ) for General λ. Machine Learning 8 (3-4), pp. 341 - 362 (1992)
  5. 225.
    Journal Article
    Watkins, C.; Dayan, P.: Q-learning. Machine Learning 8 (3-4), pp. 279 - 292 (1992)
  6. 226.
    Journal Article
    Dayan, P.; Willshaw, D.: Optimising synaptic learning rules in linear associative memories. Biological Cybernetics 65 (4), pp. 253 - 265 (1991)
  7. 227.
    Journal Article
    Willshaw, D.; Dayan, P.: Optimal Plasticity from Matrix Memories: What Goes Up Must Come Down. Neural computation 2 (1), pp. 85 - 93 (1990)

Book (1)

  1. 228.
    Book
    Dayan, P.; Abbott, L.: Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems. MIT Press, Cambridge, MA, USA (2001), 460 pp.

Book Chapter (3)

  1. 229.
    Book Chapter
    Dayan, P.: Exploration from Generalization Mediated by Multiple Controllers. In: Intrinsically Motivated Learning in Natural and Artificial Systems, pp. 73 - 91 (Eds. Baldassarre, G.; Mirolli, M.). Springer, Berlin, Germany (2013)
  2. 230.
    Book Chapter
    Dayan, P.: Models of Value and Choice. In: Neuroscience of Preference and Choice: Cognitive and Neural Mechanisms, pp. 33 - 52 (Eds. Dolan, R.; Sharot, T.). Elsevier/Academic Press, London, UK (2012)
  3. 231.
    Book Chapter
    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 (Eds. Engel, C.; Singer, W.). MIT Press, Cambridge, MA, USA (2008)

Proceedings (1)

  1. 232.
    Proceedings
    Exploration and Curiosity in Robot Learning and Inference (Dagstuhl Reports, 1). Dagstuhl Seminar 11131, Dagstuhl, Germany, March 27, 2011 - April 01, 2011. (2011)

Conference Paper (67)

  1. 233.
    Conference Paper
    Dezfouli , A.; Ashtiani , H.; Ghattas, O.; Nock, R.; Dayan, P.; Ong, C.: Disentangled behavioural representations. In: Advances in Neural Information Processing Systems 32 (Eds. Wallach, H.; Larochelle, H.; Beygelzimer , A.; d'Alché-Buc, F.; Fox, E. et al.). Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada, December 09, 2019 - December 13, 2019. (2019)
  2. 234.
    Conference Paper
    Jain, Y.; Gupta, S.; Rakesh, V.; Dayan, P.; Callaway, F.; Lieder, F.: How do people learn how to plan? In: Conference on Cognitive Computational Neuroscience (CCN 2019). Conference on Cognitive Computational Neuroscience (CCN 2019), Berlin, Germany, September 13, 2019 - September 16, 2019. (2019)
  3. 235.
    Conference Paper
    Browning, M.; Carter, C.; Chatham, C.; Den Ouden, H.; Gillan, C.; Baker, J.; Chekroud, A.; Cools, R.; Dayan, P.; Gold, J. et al.; Goldstein, R.; Hartley, C.; Kepecs, A.; Lawson, R.; Mourao-Miranda, J.; Phillips, M.; Pizzagalli, D.; Powers, A.; Rindskopf, D.; Roiser, J.; Schmack, K.; Schiller, D.; Sebold, M.; Stephan, K.; Frank, M.; Huys, Q.; Paulus, M.: Realizing the Clinical Potential of Computational Psychiatry: Report from the Banbury Center Meeting, February 2019. In: Banbury Center Meeting. Banbury Center Meeting, Huntington, NY, USA, 2019-02. (2019)
  4. 236.
    Conference Paper
    Dezfouli, A.; Morris, R.; Ramos, F.; Dayan, P.; Balleine, B.: Integrated accounts of behavioral and neuroimaging data using flexible recurrent neural network models. In: Advances in Neural Information Processing Systems 31, pp. 4233 - 4242 (Eds. Bengio, S.; Wallach, H.; Larochelle, H.; Grauman, K.; Cesa-Bianchi, N. et al.). 32nd Annual Conference on Neural Information Processing Systems (NeurIPS 2018), Montréal, Canada, December 03, 2018 - December 08, 2018. Curran, Red Hook, NY, USA (2019)
  5. 237.
    Conference Paper
    Ahilan, S.; Dayan, P.: Feudal Multi-Agent Hierarchies for Cooperative Reinforcement Learning. In: Annual Conference of the American Library Association (ALA 2019). Annual Conference of the American Library Association (ALA 2019) , Washington, DC, USA, June 20, 2019 - June 25, 2019. (2019)
  6. 238.
    Conference Paper
    Ahilan, S.; Dayan, P.: Feudal Multi-Agent Hierarchies for Cooperative Reinforcement Learning. In: Workshop on Structure & Priors in Reinforcement Learning (SPiRL 2019) at ICLR 2019. Workshop on Structure & Priors in Reinforcement Learning (SPiRL 2019) at ICLR 2019, New Orleans, LA, USA, May 06, 2019. (2019)
  7. 239.
    Conference Paper
    Stojic, H.; Eldar, E.; Bassam, H.; Dayan, P.; Dolan, R.: Are you sure about that? On the origins of confidence in concept learning. In: Conference on Cognitive Computational Neuroscience (CCN 2018). Conference on Cognitive Computational Neuroscience (CCN 2018), Philadelphia, PA, USA, September 05, 2018 - September 08, 2018. (2018)
  8. 240.
    Conference Paper
    Karaletsos, T.; Dayan, P.; Ghahramani, Z.: Probabilistic Meta-Representations Of Neural Networks. In: CAST's 4th Annual UDL Symposium: Empowering Learners. CAST's 4th Annual UDL Symposium: Empowering Learners , Cambridge, MA, USA, July 30, 2018 - August 01, 2018. (2018)
Go to Editor View