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Braitenberg, V.; Caianiello, E. (Eds.): Ricerche teoriche e sperimentali di cibernetica svolte nell'anno accademico 1961-1962 nel Laboritorio di cibernetica presso l'Istitutio di fisica teorica dell'Università di Napoli (Quaderni de la ricerca scientifica, 11). Ricerche teoriche e sperimentali di cibernetica svolte nell'anno accademico 1961-1962 nel Laboritorio di cibernetica presso l'Istitutio di fisica teorica dell'Università di Napoli, Napoli, Italy. Consiglio Nazionale delle Ricerche, Roma, Italy (1964), 71 pp.

Wu, S.; Alaniz, S.; Karthik, S.; Dayan, P.; Schulz, E.; Akata, Z.: Concept-Guided Interpretability via Neural Chunking. In: Thirty-ninth Conference on Neural Information Processing Systems (NeurIPS 2025). Thirty-ninth Conference on Neural Information Processing Systems (NeurIPS 2025), Vancouver, Canada, December 10, 2024 - December 15, 2024. (2025)

Nagy, D.; Shen, K.; Zhou, H.; Wu, C.; Dayan, P.: Analogy making as amortised model construction. In: Second Reinforcement Learning Conference (RLC 2025). Second Reinforcement Learning Conference (RLC 2025), Edmonton, AB, Canada, August 05, 2025 - August 09, 2025. (2025)

Nath, S.; del Cuvillo y Schröder, G.; Stevenson, C.: Pencils to Pixels: A Systematic Study of Creative Drawings across Children, Adults and AI. In: Proceedings of the 47th Annual Conference of the Cognitive Science Society, T.14.4, pp. 1123 - 1130 (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)

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)

Demircan, C.; Saanum, T.; Pettini, L.; Binz, M.; Baczkowski, B.; Doeller, C.; Garvert, M.; Schulz, E.: Evaluating alignment between humans and neural network representations in image-based learning tasks. In: NIPS '24: Proceedings of the 38th International Conference on Neural Information Processing Systems, 3890, pp. 122406 - 122433 (Eds. Globerson, A.; Mackey, L.; Belgrave, D.; Fan, A.; Paquet, U. et al.). Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024), Vancouver, Canada, December 11, 2024 - December 15, 2024. Curran, Red Hook, NY, USA (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)

Demircan, C.; Saanum, T.; Jagadish, A.; Binz, M.; Schulz, E.: Sparse Autoencoders Reveal Temporal Difference Learning in Large Language Models. 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)

Gholamzadeh, A.; Sajid, N.: Model alignment using inter-modal bridges. 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)

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)

Rachum, R.; Nakar, Y.; Tomlinson, B.; Alon, N.; Mirsky, R.: Emergent Dominance Hierarchies in Reinforcement Learning Agents. In: Coordination, Organizations, Institutions, Norms, and Ethics for Governance of Multi-Agent Systems XVII: International Workshop, COINE 2024, Auckland, New Zealand, May 7, 2024, pp. 41 - 56 (Eds. Cranefield, S.; Nardin, L.; Lloyd, N.). International Workshop Coordination, Organizations, Institutions, Norms, and Ethics for Governance of Multi-Agent Systems XVII (COINE 2024) , Auckland, New Zealand, May 07, 2024. Springer, Cham, Switzerland (2025)

Chen, J.; Teng, T.; Shao, Y.; Zhang, H.: Why some simple probabilistic rules are difficult to learn: A hypothesis diffusion model. In: 2024 Conference on Cognitive Computational Neuroscience, C85. Conference on Cognitive Computational Neuroscience (CCN 2024), Boston, MA, USA, August 06, 2024 - August 09, 2024. (2024)

Lu, H.; Teng, T.; Zhang, H.: The Development of Superstitions in Uncontrollable Environment. In: 2024 Conference on Cognitive Computational Neuroscience, A8. 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: 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)

Brändle, F.; Kessler, S.; Ruggeri, A.; Schulz, E.: Uncertainty-driven little alchemists: Differences in exploration strategies between adults and children in an online game. In: 46th Annual Conference of the Cognitive Science Society (CogSci 2024). 46th Annual Conference of the Cognitive Science Society (CogSci 2024), Rotterdam, The Netherlands, July 24, 2024 - July 27, 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)