Publications of P Dayan

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)

Shen, T.; Dayan, P.: Risking your Tail: Curiosity, Danger & Exploration. In: 2023 Conference on Cognitive Computational Neuroscience, P-3.67, pp. 1113 - 1116. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, August 24, 2023 - August 27, 2023. (2023)

Shen, T.; Dayan, P.; Bányai, M.: Meta-cognitive planning for learning representations. In: 2023 Conference on Cognitive Computational Neuroscience, P-2.1, pp. 425 - 428. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, August 24, 2023 - August 27, 2023. (2023)

Alon, N.; Schulz, L.; Dayan, P.; Barnby, J.: Between prudence and paranoia: Theory of Mind gone right, and wrong. In: ICML 2023: First Workshop on Theory of Mind in Communicating Agents (ToM 2023). ICML 2023: First Workshop on Theory of Mind in Communicating Agents (ToM 2023), Honolulu, HI,USA, July 28, 2023. (2023)

Éltetö, N.; Dayan, P.: Habits of Mind: Reusing Action Sequences for Efficient Planning. 45th Annual Meeting of the Cognitive Science Society (CogSci 2023): Workshop "Compositionality in minds, brains and machines: a unifying goal that cuts across cognitive sciences", Sydney, Australia, July 26, 2023 - July 29, 2023. Proceedings of the Annual Meeting of the Cognitive Science Society 45, pp. 195 - 201 (2023)

Rubino, V.; Hamidi, M.; Dayan, P.; Wu, C.: Compositionality under time pressure. 45th Annual Meeting of the Cognitive Science Society (CogSci 2023), Sydney, Australia, July 26, 2023 - July 29, 2023. Proceedings of the Annual Meeting of the Cognitive Science Society 45, pp. 678 - 685 (2023)

Schulz, L.; Alon, N.; Rosenschein, J.; Dayan, P.: Emergent deception and skepticism via theory of mind. In: ICML 2023: First Workshop on Theory of Mind in Communicating Agents (ToM 2023). ICML 2023: First Workshop on Theory of Mind in Communicating Agents (ToM 2023), Honolulu, HI,USA, July 28, 2023. (submitted)

Alon, N.; Schulz, L.; Rosenschein, J.; Dayan, P.: A (dis-)information theory of revealed and unrevealed preferences. In: Information-Theoretic Principles in Cognitive Systems: Workshop at the 36th Conference on Neural Information Processing Systems (NeurIPS 2022). NeurIPS 2022 Workshop on Information-Theoretic Principles in Cognitive Systems, New Orleans, LA, USA, December 03, 2022. (2022)

Bruijns, S.; The International Brain Laboratory; Dayan, P.: Understanding Learning Trajectories With Infinite Hidden Markov Models. In: 2022 Conference on Cognitive Computational Neuroscience, P-1.19, pp. 64 - 66. Conference on Cognitive Computational Neuroscience (CCN 2022), San Francisco, CA, USA, August 25, 2022 - August 28, 2022. (2022)