Publications of P Dayan

Dayan, P.: Helmholtz machines and wake-sleep learning. In: The Handbook of Brain Theory and Neural Networks, 2. Ed., pp. 522 - 524 (Ed. Arbib, M.). MIT Press, Cambridge, MA, USA (2003)

Schraudolph, N.; Dayan, P.; Sejnowski, T.: Learning to Evaluate Go Positions via Temporal Difference Methods. In: Computational Intelligence in Games, pp. 77 - 98 (Eds. Baba, N.; Jain, L.). Physica Verlag, Heidelberg, Germany (2001)

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)

Graham, T.; Doeller, C.; Dayan, P.: Beyond directedness: Efficient meta-exploration during multi-step planning. In: Finding the Frame Workshop at RLC 2026. RLC 2026: Workshop Finding the Frame, Montréal, Canada, August 15, 2026. (2026)

Zaghw, K.; Dayan, P.; Antonov, G.: Weight a moment: risk-aware exploration with Bayes. Reinforcement Learning Conference (RLC 2026), Montréal, Canada, August 15, 2026 - August 17, 2026. Reinforcement Learning Journal 7, (2026)

Chebolu, S.; Zhang, P.; Ma, W.; Dayan, P.: Now or later: A reinforcement learning model of behavioural delay. In: Proceedings of the Annual Meeting of the Cognitive Science Society, Vol. 48, FT.32.9, pp. 2193 - 2199 (Eds. Boleda, G.; Dautriche, I.; Maldonado, M.; Saldana, C.; Torrent, T.). 48th Annual Meeting of the Cognitive Science Society (CogSci 2026), Rio de Janeiro, Brazil, July 22, 2026 - August 25, 2026. (2026)

Wu, S.; Alaniz, S.; Karthik, S.; Dayan, P.; Schulz, E.; Akata, Z.: Concept-Guided Interpretability via Neural Chunking. In: Advances in Neural Information Processing Systems 38 (NeurIPS 2025), pp. 72886 - 72932 (Eds. Belgrave, D.; Zhang, C.; Lin, H.; Pascanu, R.; Koniusz, P. et al.). Thirty-ninth Conference on Neural Information Processing Systems (NeurIPS 2025), San Diego, CA, USA ; Mexico City, Mexico, December 02, 2025 - December 07, 2025. Curran, Red Hook, NY, USA (2026)

Nagy, D.; Shen, T.; Zhou, H.; Wu, C.; Dayan, P.: Analogy making as amortised model construction. In: Finding the Frame Workshop at RLC 2025. Finding the Frame Workshop at RLC 2025, Edmonton, AB, Canada, August 05, 2025. (2025)

Sarıtaş, K.; Dayan, P.; Shen, K.; Nath, S.: Complexity in Complexity: Understanding Visual Complexity Through Structure, Color, and Surprise. In: Proceedings of the 47th Annual Conference of the Cognitive Science Society, V5-S-60, pp. 2623 - 2630 (Eds. Barner, D.; Bramley, N.; Ruggeri, A.; Walker, C.). 47th Annual Meeting of the Cognitive Science Society (CogSci 2025): Theories of the Past, Theories of the Future , San Francisco, CA, USA, July 30, 2025 - August 02, 2025. (2025)

Saanum, T.; Dayan, P.; Schulz, E.: Simplifying Latent Dynamics with Softly State-Invariant World Models. In: NIPS '24: Proceedings of the 38th International Conference on Neural Information Processing Systems, 1212, pp. 38355 - 38382 (Eds. Globerson, A.; Mackay, L.; Belgrave, D.; Fan, A.; Paquet, U. et al.). Thirty-eighth Conference on Neural Information Processing Systems (NeurIPS 2024), Vancouver, Canada, December 10, 2024 - December 15, 2024. Curran, Red Hook, NY, USA (2025)

Saanum, T.; Schulze Buschoff, L.; Dayan, P.; Schulz, E.: Next state prediction gives rise to entangled, yet compositional representations of objects. In: Thirteenth International Conference on Learning Representations (ICLR 2025). Thirteenth International Conference on Learning Representations (ICLR 2025), Singapore, April 24, 2025 - April 28, 2025. (2025)

Sarıtaş, K.; Dayan, P.; Shen, K.; Nath, S.: Complexity in Complexity: Understanding Visual Complexity Through Structure, Color, and Surprise. In: ICLR 2025 Workshop on Representational Alignment (Re-Align). ICLR 2025 Workshop on Representational Alignment (Re-Align), Singapore, April 28, 2025. (2025)

Wu, S.; Thalmann, M.; Dayan, P.; Akata, Z.; Schulz, E.: Building, Reusing, and Generalizing Abstract Representations from Concrete Sequences. In: Thirteenth International Conference on Learning Representations (ICLR 2025). Thirteenth International Conference on Learning Representations (ICLR 2025), Singapore, April 24, 2025 - April 28, 2025. (2025)

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), P3-L-638, 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)