Publications of P Dayan

Dayan, P.: Unsupervised Learning. In: The MIT Encyclopedia of the Cognitive Sciences (Eds. Wilson, R.; Keil, F.). MIT Press, Cambridge, MA, USA (1999)

Montague, P.; Dayan, P.: Neurobiological Modeling: Squeezing Top Down to Meet Bottom Up. In: A Companion to Cognitive Science, pp. 526 - 542 (Eds. Bechtel, W.; Graham, G.). Blackwell, Malden, MA, USA (1998)

Oberlander, J.; Dayan, P.: Altered states and virtual beliefs. In: Connectionism, Concepts and Folk Psychology: The Legacy of Alan Turing Vol. 2, pp. 101 - 114 (Eds. 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, March 27, 2011 - April 01, 2011. (2011)

Satti, M.; Wille, K.; Nassar, M.; Cichy, R.; Schuck, N.; Dayan, P.; Bruckner, R.: Absence of systematic effects of trait anxiety on learning under uncertainty. In: 7th Annual Conference on Cognitive Computational Neuroscience (CCN 2024). 7th Annual Conference on Cognitive Computational Neuroscience (CCN 2024), Boston, MA, USA, August 06, 2024 - August 09, 2024. (2024)

Satti, M.; Wille, K.; Nassar, M.; Cichy, R.; Schuck, N.; Dayan, P.; Bruckner, R.: Absence of Systematic Effects of Trait Anxiety on Learning Under Uncertainty. In: 2024 Conference on Cognitive Computational Neuroscience, B27. Conference on Cognitive Computational Neuroscience (CCN 2024), Boston, MA, USA, August 06, 2024 - August 09, 2024. (2024)

Sui, X.; Dayan, P.; Lloyd, K.: Exploring Optimal Risk-Sensitive Behavior in the Balloon Analogue Risk Task (BART). In: 2024 Conference on Cognitive Computational Neuroscience, A30. Conference on Cognitive Computational Neuroscience (CCN 2024), Boston, MA, USA, August 06, 2024 - August 09, 2024. (2024)

Chebolu, S.; Dayan, P.: Optimal and sub-optimal temporal decisions can explain procrastination in a real-world task. In: 46th Annual Meeting of the Cognitive Science Society (CogSci 2024), pp. 3102 - 3108. 46th Annual Meeting of the Cognitive Science Society (CogSci 2024) , Rotterdam, The Netherlands, July 24, 2024 - July 27, 2024. (2024)

Nazemorroaya, A.; Bang, D.; Dayan, P.: State-Independent and State-Dependent Learning in a Motivational Go/NoGo task. In: 46th Annual Conference of the Cognitive Science Society (CogSci 2024), pp. 2171 - 2178. 46th Annual Conference of the Cognitive Science Society (CogSci 2024), Rotterdam, The Netherlands, July 24, 2024 - July 27, 2024. (2024)

Shen, T.; Nath, S.; Brielmann, A.; Dayan, P.: Simplicity in Complexity: Explaining Visual Complexity using Deep Segmentation Models. In: 46th Annual Conference of the Cognitive Science Society (CogSci 2024), pp. 2017 - 2024. 46th Annual Conference of the Cognitive Science Society (CogSci 2024), Rotterdam, The Netherlands, July 24, 2024 - July 27, 2024. (2024)

Nath, S.; Dayan, P.; Stevenson, C.: Characterising the Creative Process in Humans and Large Language Models. In: 15th International Conference on Computational Creativity: ICCC'24, 179. 15th International Conference on Computational Creativity (ICCC 2024), Jönköping, Sweden, June 17, 2024 - June 21, 2024. (2024)

Nath, S.; Shen, K.; Brielmann, A.; Dayan, P.: Simplicity in Complexity. In: ICLR 2024 Workshop on Representational Alignment (Re-Align). ICLR 2024 Workshop on Representational Alignment (Re-Align), Wien, Austria, May 11, 2024. (2024)

Saanum, T.; Éltetö, N.; Dayan, P.; Binz, M.; Schulz, E.: Reinforcement Learning with Simple Sequence Priors. In: Advances in Neural Information Processing Systems 36: 37th Conference on Neural Information Processing Systems (NeurIPS 2023), 2710, pp. 61985 - 62005 (Eds. Oh, A.; Naumann, T.; Globerson, A.; Saenko, K.; Hardt, M. et al.). Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, LA, USA, December 10, 2023 - December 16, 2023. Curran, Red Hook, NY, USA (2024)

Antonov, G.; Dayan, P.: Exploring Uncertainty in Distributional Reinforcement Learning. Reinforcement Learning Conference (RLC 2024), Amherst, MA, USA, August 09, 2024 - August 12, 2024. Reinforcement Learning Journal 2, pp. 961 - 978 (2024)

Bucher, S.; Dayan, P.: Cognitive Information Filters: Algorithmic Choice Architecture for Boundedly Rational Consumers. In: NeurIPS 2023 workshop: Information-Theoretic Principles in Cognitive Systems: InfoCog@NeurIPS2023. NeurIPS 2023 workshop: Information-Theoretic Principles in Cognitive Systems: InfoCog@NeurIPS2023, New Orleans, LA, USA, December 15, 2023. (2023)

Bruijns, S.; Dayan, P.; The International Brain Laborartory: Understanding Learning Trajectories With Infinite Hidden Markov Models. In: 2023 Conference on Cognitive Computational Neuroscience, P-2.97, pp. 770 - 772. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, August 24, 2023 - August 27, 2023. (2023)

Ershadmanesh, S.; Gholamzadeh, A.; Desender, K.; Dayan, P.: Meta-cognitive Efficiency in Learned Value-based Choice. In: 2023 Conference on Cognitive Computational Neuroscience, P-1A.9, pp. 29 - 32. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, August 24, 2023 - August 27, 2023. (2023)

Renz, F.; Grossman, S.; Schuck, N.; Dayan, P.; Doeller, C.: Learning and adapting cognitive maps for flexible decision-making. In: 2023 Conference on Cognitive Computational Neuroscience, P-3.35, pp. 999 - 1001. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, August 24, 2023 - August 27, 2023. (2023)

Rubino, V.; Dayan, P.; Wu, C.: Biases towards compositionally simpler hypotheses are robust and unaffected by learning. In: 2023 Conference on Cognitive Computational Neuroscience, P-2B.50, pp. 817 - 820. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, August 24, 2023 - August 27, 2023. (2023)

Safavi, S.; Dayan, P.: A decision-theoretic model of perceptual multistability: perceptual switches as internal actions. In: 2023 Conference on Cognitive Computational Neuroscience, P-3.41, pp. 1022 - 1024. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, August 24, 2023 - August 27, 2023. (2023)