Publikationen: 
Computational Principles of Intelligence

Zeitschriftenartikel (8)

1.
Zeitschriftenartikel
Haridi, S.; Wu, C.; Dasgupta, I.; Schulz, E.: The scaling of mental computation in a sorting task. Cognition 241, 105605 (2023)
2.
Zeitschriftenartikel
Binz, M.; Dasgupta, I.; Jagadish, A.; Botvinick, M.; Wang, J.; Schulz, E.: Meta-Learned Models of Cognition. Behavioral and Brain Sciences Epub ahead (2023)
3.
Zeitschriftenartikel
Giron, A.; Ciranka, S.; Schulz, E.; van den Bos, W.; Ruggeri, A.; Meder, B.; Wu, C.: Developmental changes in exploration resemble stochastic optimization. Nature Human Behaviour 7 (11), S. 1955 - 1967 (2023)
4.
Zeitschriftenartikel
Binz, M.; Schulz, E.: Reconstructing the Einstellung effect. Computational Brain & Behavior 6 (3), S. 526 - 542 (2023)
5.
Zeitschriftenartikel
Brändle, F.; Stocks, L.; Tenenbaum, J.; Gershman, S.; Schulz, E.: Empowerment contributes to exploration behaviour in a creative video game. Nature Human Behaviour 7 (9), S. 1481 - 1489 (2023)
6.
Zeitschriftenartikel
Wu, S.; Éltetö, N.; Dasgupta, I.; Schulz, E.: Chunking as a rational solution to the speed-accuracy trade-off in a serial reaction time task. Scientific Reports 13, 7680 (2023)
7.
Zeitschriftenartikel
Garvert, M.; Saanum, T.; Schulz, E.; Schuck, N.; Doeller, C.: Hippocampal spatio-predictive cognitive maps adaptively guide reward generalization. Nature Neuroscience 26 (4), S. 615 - 626 (2023)
8.
Zeitschriftenartikel
Binz, M.; Schulz, E.: Using cognitive psychology to understand GPT-3. Proceedings of the National Academy of Sciences of the United States of America 120 (6), e2218523120 (2023)

Konferenzbeitrag (15)

9.
Konferenzbeitrag
Schreiber, A.; Wu, S.; Wu, C.; Indiveri, G.; Schulz, E.: Biologically-plausible hierarchical chunking on mixed-signal neuromorphic hardware. In: NeurIPS 2023 Workshop: Machine Learning with New Compute Paradigms. NeurIPS 2023 Workshop: Machine Learning with New Compute Paradigms, New Orleans, LA, USA, 16. Dezember 2023. (2023)
10.
Konferenzbeitrag
Coda-Forno, J.; Binz, M.; Akata, Z.; Botvinick, M.; Wang, J.; Schulz, E.: Meta-in-context learning in large language models. In: Advances in Neural Information Processing Systems 36: 37th Conference on Neural Information Processing Systems (NeurIPS 2023). Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, LA, USA, 10. Dezember 2023 - 16. Dezember 2023. (2023)
11.
Konferenzbeitrag
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). Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, LA, USA, 10. Dezember 2023 - 16. Dezember 2023. (2023)
12.
Konferenzbeitrag
Salewski, L.; Alaniz, S.; Rio-Torto, I.; Schulz, E.; Akata, Z.: In-Context Impersonation Reveals Large Language Models’ Strengths and Biases. In: Advances in Neural Information Processing Systems 36: 37th Conference on Neural Information Processing Systems (NeurIPS 2023). Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, LA, USA, 10. Dezember 2023 - 16. Dezember 2023. (2023)
13.
Konferenzbeitrag
Brändle, F.; Schulz, E.; Wu, C.: Learning progress and uncompensated rewards as motivational drivers of engagement. In: 2023 Conference on Cognitive Computational Neuroscience, P-2.114, S. 832 - 835. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)
14.
Konferenzbeitrag
Haridi, S.; Thalmann, M.; Schulz, E.: Simulating the Scaling of Long-Term Memory Retrieval. In: 2023 Conference on Cognitive Computational Neuroscience, P-2.101, S. 784 - 787. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)
15.
Konferenzbeitrag
Hedrich, N.; Hall-McMaster, S.; Schulz, E.; Schuck, N.: Faster learning from slow features: The temporal coherence prior in human reinforcement learning. In: 2023 Conference on Cognitive Computational Neuroscience, P-2.10, S. 458 - 461. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)
16.
Konferenzbeitrag
Ludwig, T.; Siegel, M.; Schulz, E.: Human Multi-Task Learning: the Why and What. In: 2023 Conference on Cognitive Computational Neuroscience, P-1.119, S. 418 - 421. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)
17.
Konferenzbeitrag
Schubert, J.; Jagadish, A.; Binz, M.; Schulz, E.: A Rational Analysis of the Optimism Bias using Meta-Reinforcement Learning. In: 2023 Conference on Cognitive Computational Neuroscience, P-2.37, S. 557 - 559. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)
18.
Konferenzbeitrag
Schulze Buschoff, L.; Schulz, E.; Binz, M.: The Acquisition of Physical Knowledge in Generative Neural Networks. In: 40th International Conference on Machine Learning, S. 30321 - 30341 (Hg. Krause, A.; Brunskill, E.; Cho, K.; Engelhardt, B.; Sabato, S. et al.). Fortieth International Conference on Machine Learning (ICML 2023), Honolulu, HI,USA, 23. Juli 2023 - 29. Juli 2023. (2023)
19.
Konferenzbeitrag
Thalmann, M.; Schulz, E.: Simple, Idiosyncratic Decision Heuristics in a Two-Armed Bandit Task. In: 2023 Conference on Cognitive Computational Neuroscience, P-3.80, S. 1156 - 1159. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)
20.
Konferenzbeitrag
Witte, K.; Schulz, E.; Wise, T.; Huys, Q.: People who worry more explore more. In: 2023 Conference on Cognitive Computational Neuroscience, P-1.101, S. 355 - 357. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)
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