Publikationen von E Schulz

Zeitschriftenartikel (34)

21.
Zeitschriftenartikel
Dasgupta, I.; Schulz, E.; Tenenbaum, J.; Gershman, S.: A theory of learning to infer. Psychological Review 127 (3), S. 412 - 441 (2020)
22.
Zeitschriftenartikel
Stojic, H.; Schulz, E.; Analytis, P.; Speekenbrink, M.: It's new, but is it good? How generalization and uncertainty guide the exploration of novel options. (eingereicht)
23.
Zeitschriftenartikel
Schulz, E.; Wu, C.; Ruggeri, A.; Meder, B.: Searching for rewards like a child means less generalization and more directed exploration. Psychological Science 30 (11), S. 1561 - 1572 (2019)
24.
Zeitschriftenartikel
Schulz, E.; Bhui, R.; Love, B.; Brier, B.; Todd, M.; Gershman, S.: Structured, uncertainty-driven exploration in real-world consumer choice. Proceedings of the National Academy of Sciences of the United States of America 116 (28), S. 13903 - 13908 (2019)
25.
Zeitschriftenartikel
Schulz, E.; Gershman, S.: The algorithmic architecture of exploration in the human brain. Current Opinion in Neurobiology 55, S. 7 - 14 (2019)
26.
Zeitschriftenartikel
Wu, C.; Schulz, E.; Speekenbrink, M.; Nelson, J.; Meder, B.: Generalization guides human exploration in vast decision spaces. Nature Human Behaviour 2 (12), S. 915 - 924 (2018)
27.
Zeitschriftenartikel
Schulz, E.; Wu, C.; Huys, Q.; Krause, A.; Speekenbrink, M.: Generalization and search in risky environments. Cognitive Science 42 (8), S. 2592 - 2620 (2018)
28.
Zeitschriftenartikel
Dasgupta, I.; Schulz, E.; Goodman, N.; Gershman , S.: Remembrance of Inferences Past: Amortization in Human Hypothesis Generation. Cognition 178, S. 67 - 81 (2018)
29.
Zeitschriftenartikel
Schulz, E.; Speekenbrink, M.; Krause, A.: A tutorial on Gaussian process regression: Modelling, exploring, and exploiting functions. Journal of Mathematical Psychology 85, S. 1 - 16 (2018)
30.
Zeitschriftenartikel
Schulz, E.; Konstantinidis, E.; Speekenbrink, M.: Putting Bandits Into Context: How Function Learning Supports Decision Making. Journal of Experimental Psychology: Learning, Memory, and Cognition 44 (6), S. 927 - 943 (2018)
31.
Zeitschriftenartikel
Schulz, E.; Tenenbaum, J.; Duvenaud, D.; Speekenbrink , M.; Gershman, S.: Compositional Inductive Biases in Function Learning. Cognitive Neuroscience 99, S. 44 - 79 (2017)
32.
Zeitschriftenartikel
Dasgupta, I.; Schulz, E.; Gershman, S.: Where Do Hypotheses Come From? Cognitive Psychology 96, S. 1 - 25 (2017)
33.
Zeitschriftenartikel
Cokely, E.; Galesic, M.; Schulz, E.; Ghazal, S.; Garcia-Retamero, R.: Measuring risk literacy: The Berlin numeracy test. Judgment and Decision Making 7 (1), S. 25 - 47 (2012)
34.
Zeitschriftenartikel
Schulz, E.; Cokely, E.; Feltz, A.: Persistent bias in expert judgments about free will and moral responsibility: A test of the expertise defense. Consciousness and Cognition 20 (4), S. 1722 - 1731 (2011)

Buch (1)

35.
Buch
Cogliati Dezza, I.; Wu, C.; Schulz, E.: The Drive for Knowledge: The Science of Human Information-Seeking. Cambridge University Press, Cambridge, UK (2022), 292 S.

Buchkapitel (3)

36.
Buchkapitel
Brändle, F.; Binz, M.; Schulz, E.: Exploration beyond bandits. In: The Drive for Knowledge: The Science of Human Information-Seeking, S. 147 - 168 (Hg. Cogliati Dezza, I.; Wu, C.; Schulz, E.). Cambridge University Press, Cambridge, UK (2022)
37.
Buchkapitel
Cogliati Dezza, I.; Schulz, E.; Wu, C.: Future challenges. In: The drive for knowledge: The science of human information seeking, S. 279 - 290 (Hg. Cogliati Dezza, I.; Schulz, E.; Wu, C.). Cambridge University Press, Cambridge, UK (2022)
38.
Buchkapitel
Cokely, E.; Ghazal, S.; Galesic, M.; García-Retamero, R.; Schulz, E.: How to measure risk comprehension in educated samples. In: Transparent communication of health risks: Overcoming cultural differences, S. 29 - 52. Springer, New York, NY, USA (2013)

Konferenzbeitrag (46)

39.
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)
40.
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)
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