Publications

Google scholar page

Publications:

Working papers:

Schulz, E. (finally submitted). Towards a unifying model of generalization. PhD-thesis.

Wu, C.M., Schulz, E., Speekenbrink, M., Nelson, J.D., & Meder, B. (submitted). Exploration and generalization in vast spaces.

Schulz, E., Speekenbrink, M., & Krause, A. (submitted). A tutorial on Gaussian process regression with a focus on exploration-exploitation scenarios. [PDF]

Schulz, E., Tenenbaum, J.B., Duvenaud, D., Speekenbrink, M., & Gershman, S.J. (submitted). Compositional Inductive Biases in Function Learning. [PDF]

2017:

Schulz, E., Konstantinidis, E., & Speekenbrink, M. (accepted). Putting bandits into context: How function learning supports decision making. Journal of Experimental Psychology: Learning, Memory, and Cognition. [PDF]

Dasgupta, I., Schulz, E., & Gershman, S.J. (2017). Where do hypotheses come from? Cognitive Psychology. Cognitive Psychology, 96, 1-25. [PDF]

Schulz, E., Klenske, E.D., Bramley, N.R., & Speekenbrink, M. (2017). Strategic exploration in human adaptive control. Proceedings of the Thirty-Ninth Annual Conference of the Cognitive Science Society. [PDF]

Wu, C.M., Schulz, E., Speekenbrink, M., Nelson, J.D., & Meder, B. (2017). Mapping the unknown: The spatially correlated multi-armed bandit.  Proceedings of the Thirty-Ninth Annual Conference of the Cognitive Science Society. [PDF]

Dasgupta, I., Schulz, E., Goodman, N.D., & Gershman, S.J. (2017).  Amortized Hypothesis Generation.  Proceedings of the Thirty-Ninth Annual Conference of the Cognitive Science Society. [PDF]

2016:

[12] Schulz, E., Speekenbrink, M., Hernández Lobato J. M., Ghahramani, Z., & Gershman, S.J. (2016). Quantifying mismatch in Bayesian optimization. In NIPS Workshop on Bayesian Optimization: Black-box Optimization and beyond, Barcelona, Spain, 2016. [PDF]

[11] Schulz, E., Tenenbaum, J.B., Duvenaud, D., Speekenbrink, M., & Gershman, S.J. (2016). Probing the Compositionality of Intuitive Functions.  In Advances in Neural Information Processing Systems. [PDF]

[10] Schulz, E., Huys, Q. J. M., Bach, D.R., Speekenbrink, M., & Krause, A. (2016). Better safe than sorry: Risky function exploitation through safe optimization. Proceedings of the Thirty-Eighth Annual Conference of the Cognitive Science Society. [PDF]

[9] Schulz, E., Speekenbrink, M., & Meder, B. (2016). Simple trees in complex forests:
Growing Take The Best by Approximate Bayesian Computation. Proceedings of the Thirty-Eighth Annual Conference of the Cognitive Science Society. [PDF]

2015:

[8] Schulz, E., Konstantinidis, E., & Speekenbrink, M. (2015). Learning and decisions in contextual multi-armed bandit tasks. Proceedings of the Thirty-Seventh Annual Conference of the Cognitive Science Society. [PDF]

[7] Schulz, E., Tenenbaum, J.B., Reshef, D.N., Speekenbrink, M., & Gershman, S.J. (2015). Assessing the perceived predictability of functions. Proceedings of the Thirty-Seventh Annual Conference of the Cognitive Science Society. [PDF]

[6] Parpart, P., Schulz, E., Speekenbrink, M., & Love, B.C. (2015). Active learning as a means to distinguish among prominent decision strategies. Proceedings of the Thirty-Seventh Annual Conference of the Cognitive Science Society. [PDF]

[5] Schulz, E., Konstantinidis, E., & Speekenbrink, M. (2015). Exploration-Exploitation in a Contextual Multi-Armed Bandit Task.  Proceedings of the International Conference on Cognitive Modeling. [PDF]

2014:

[4] Schulz, E., Speekenbrink, M., & Shanks, D.R. (2014). Predict choice – a comparison of 21 mathematical models. In P. Bello, M. Guarini, M. McShane, & B. Scassellati (Eds.), Proceedings of the 36th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society. [PDF]

Before 2014:

[3] Cokely, E.T., Ghazal, S., Galesic, M., Garcia-Retamero, R., & Schulz, E.(2013). How to measure risk comprehension in educated samples. Transparent Communication of Health Risks, 29-52. [PDF]

[2] Cokely E.T., Galesic, M., Schulz, E., Ghazal, S., & Garcia-Retamero, R. (2012).Measuring risk literacy: The Berlin numeracy test. Judgment and Decision Making 7 (1), 25-47. [PDF]

[1] Schulz,E., Cokely, E.T., & Feltz, A. (2011). Persistent bias in expert judgments about free will and moral responsibility: A test of the expertise defense. Consciousness and cognition 20 (4), 1722-1731. [PDF]

 

Theses:

[c] Schulz, E. (2014). Function learning as Gaussian Process optimization. Unpublished MRes-Thesis supervised by Maarten Speekenbrink.

[b] Schulz, E. (2012). Measuring the behaviour of Monte Carlo Markov chain sampling schemes. Unpublished MSc-Thesis supervised by Brian Ripley.

[a] Schulz, E. (2011). Choosing how to predict choices. Unpublished MSc-thesis supervised by Maarten Speekenbrink & David Shanks.

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