Publications of E Schulz

Jagadish, A.; Rmus, M.; Witte, K.; Mathony, M.; Binz, M.; Schulz, E.: Can we automatize scientific discovery in the cognitive sciences? (submitted)

Kipnis, A.; Binz, M.; Schulz, E.: A fast neural model for Bayesian mixed-effects regression. (submitted)

Jagadish, A.; Thalmann, M.; Coda-Forno, J.; Binz, M.; Schulz, E.: Meta-learning ecological priors from large language models explains human learning and decision making. (submitted)

Modirshanechi, A.; Dayan, P.; Schulz, E.: An integrative framework for the human sense of control. (submitted)

Rmus, M.; Jagadish, A.; Mathony, M.; Ludwig, T.; Schulz, E.: Towards Automation of Cognitive Modeling using Large Language Models. (submitted)

Vélez, N.; Wu, C.; Gershman, S.; Schulz, E.: The rise and fall of technological development in virtual communities. (submitted)

Hagendorff, T.; Dasgupta, I.; Binz, M.; Chan, S.; Lampinen, A.; Wang, J.; Akata, Z.; Schulz, E.: Machine Psychology. (submitted)

Schäfer, T.; Thalmann, M.; Schulz, E.; Doeller, T.; Theves, S.: The hippocampus supports interpolation into new states during category abstraction. (submitted)

Jagadish, A.; Binz, M.; Saanum, T.; Wang, J.; Schulz, E.: Zero-shot compositional reinforcement learning in humans. (submitted)

Coda-Forno, J.; Witte, K.; Jagadish, A.; Binz, M.; Akata, Z.; Schulz, E.: Inducing anxiety in large language models increases exploration and bias. (submitted)

Schulze Buschoff, L.; Schulz, E.; Binz, M.: Stochastic Gradient Descent Captures How Children Learn About Physics. (submitted)

Binz, M.; Schulz, E.: Exploration With a Finite Brain. (submitted)

Schulz, E.: Science on film, episode 3: Computational principles of intelligence. (2020)