Publikationen von P Dayan

Oberlander, J.; Dayan, P.: Altered states and virtual beliefs. In: Connectionism, Concepts and Folk Psychology: The Legacy of Alan Turing Vol. 2, S. 101 - 114 (Hg. Millican, P.; Clark, A.). Clarendon Press, Oxford, UK (1996)

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

Gagne, C.; Dayan, P.: Two steps to risk sensitivity. In: Advances in Neural Information Processing Systems 34 (Hg. Ranzato, M.; Beygelzimer, A.; Liang, P.; Vaughan, J.; Dauphin, Y.). Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021), 06. Dezember 2021 - 14. Dezember 2021. (angenommen)

Tano, P.; Dayan, P.; Pouget, A.: A local temporal difference code for distributional reinforcement learning. In: Advances in Neural Information Processing Systems 33, S. 13662 - 13673 (Hg. Larochelle, H.; Ranzato, M.; Hadsell, R.; Balcan, M.-F.; Lin, H.-T.). 34th Conference on Neural Information Processing Systems (NeurIPS 2020), 06. Dezember 2020 - 12. Dezember 2020. Curran, Red Hook, NY, USA (2021)

Ahilan, S.; Dayan, P.: Correcting Experience Replay for Multi-Agent Communication. In: Ninth International Conference on Learning Representations (ICLR 2021). Ninth International Conference on Learning Representations (ICLR 2021), Vienna, Austria, 03. Mai 2021 - 07. Mai 2021. (2021)

Sezener, E.; Dayan, P.: Static and Dynamic Values of Computation in MCTS. 36th Conference on Uncertainty in Artificial Intelligence (UAI 2020), 03. August 2020 - 06. August 2020. Proceedings of Machine Learning Research (PMLR) 124, 26, S. 31 - 40 (2020)

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. Banbury Center Meeting 2019, Huntington, NY, USA, 2019-02. Biological Psychiatry 88 (2), S. e5 - e10 (2020)

Dezfouli, A.; Ashtiani, H.; Ghattas, O.; Nock, R.; Dayan, P.; Ong, C.: Disentangled behavioural representations. In: Advances in Neural Information Processing Systems 32, S. 2243 - 2252 (Hg. 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, 09. Dezember 2019 - 13. Dezember 2019. Curran, Red Hook, NY, USA (2020)

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), PS-2A.70, S. 826 - 829. Conference on Cognitive Computational Neuroscience (CCN 2019), Berlin, Germany, 13. September 2019 - 16. September 2019. (2019)

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, S. 4233 - 4242 (Hg. 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, 03. Dezember 2018 - 08. Dezember 2018. Curran, Red Hook, NY, USA (2019)

Ahilan, S.; Dayan, P.: Feudal Multi-Agent Hierarchies for Cooperative Reinforcement Learning. In: Annual Conference of the American Library Association (ALA 2019), 5, S. 1 - 5. Annual Conference of the American Library Association (ALA 2019) , Washington, DC, USA, 20. Juni 2019 - 25. Juni 2019. (2019)

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, S. 1 - 11. Workshop on Structure & Priors in Reinforcement Learning (SPiRL 2019) at ICLR 2019, New Orleans, LA, USA, 06. Mai 2019. (2019)

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), PS-1A.14, S. 1 - 4. Conference on Cognitive Computational Neuroscience (CCN 2018), Philadelphia, PA, USA, 05. September 2018 - 08. September 2018. (2018)

Karaletsos, T.; Dayan, P.; Ghahramani, Z.: Probabilistic Meta-Representations Of Neural Networks. In: CAST's 4th Annual UDL Symposium: Empowering Learners, S. 1 - 10. CAST's 4th Annual UDL Symposium: Empowering Learners , Cambridge, MA, USA, 30. Juli 2018 - 01. August 2018. (2018)

Rae, J.; Dyer, C.; Dayan, P.; Lillicrap, C.: Fast Parametric Learning with Activation Memorization. In: International Conference on Machine Learning, 10-15 July 2018, S. 4228 - 4237 (Hg. Dy, J.; Krasue, A.). 35th International Conference on Machine Learning (ICML 2018), Stockholm, Sweden, 10. Juli 2018 - 15. Juli 2018. International Machine Learning Society, Madison, WI, USA (2018)

Bramley, N.; Dayan, P.; Lagnado, D.: Staying afloat on Neurath's boat: Heuristics for sequential causal learning. In: 37th Annual Meeting of the Cognitive Science Society (CogSci 2015): Mind, Technology and Society, S. 262 - 267 (Hg. Noelle, D.; Dale, R.; Warlaumont, A.; Yoshimi, J.; Matlock, T. et al.). 37th Annual Meeting of the Cognitive Science Society (CogSci 2015), Pasadena, CA, USA, 22. Juli 2015 - 25. Juli 2015. Cognitive Science Society, Austin, TX, USA (2015)

Guez, A.; Heess, N.; Silver, D.; Dayan, P.: Bayes-Adaptive Simulation-based Search with Value Function Approximation. In: Advances in Neural Information Processing Systems 27 (NIPS 2014), S. 451 - 459 (Hg. Ghahramani, Z.; Welling, M.; Cortes, C.; Lawrence, N.; Weinberger, K.). Twenty-Eighth Annual Conference on Neural Information Processing Systems (NIPS 2014) , Montreal, Canada, 08. Dezember 2014 - 13. Dezember 2014. Curran, Red Hook, NY, USA (2015)

Savin, C.; Dayan, P.; Lengyel, M.: Correlations strike back (again): the case of associative memory retrieval. In: Advances in Neural Information Processing Systems 26 (NIPS 2013), S. 288 - 296 (Hg. Burges, C.; Bottou, L.; Ghahramani, Z.; Weinberger, K.). Twenty-Seventh Annual Conference on Neural Information Processing Systems (NIPS 2013), Lake Tahoe, NV, USA, 05. Dezember 2013 - 10. Dezember 2013. Curran, Red Hook, NY, USA (2014)

Gershman, S.; Tenenbaum, J.; Pouget, A.; Botvinick, M.; Dayan, P.: Structured cognitive representations and complex inference in neural systems. In: 35th Annual Meeting of the Cognitive Science Society (CogSci 2013), S. 83 - 84 (Hg. Knauff, M.; Pauen, M.; Sebanz, N.; Wachsmuth, I.). 35th Annual Meeting of the Cognitive Science Society (CogSci 2013), Berlin, Germany, 31. Juli 2013 - 03. August 2013. Cognitive Science Society, Austin, TX, USA (2013)

Guez, A.; Silver, D.; Dayan, P.: Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search. In: Advances in Neural Information Processing Systems 25, S. 1025 - 1033 (Hg. Bartlett, P.; Pereira, F.; Bottou, L.; Burgess, C.; Weinberger, K.). Twenty-Sixth Annual Conference on Neural Information Processing Systems (NIPS 2012) , Lake Tahoe, NV, USA, 03. Dezember 2012 - 06. Dezember 2012. Curran, Red Hook, NY, USA (2013)