Lasse Elsemüller, M.Sc.

Doctoral Candidate

University of Heidelberg
Hauptstr. 47, Room F023
69117 Heidelberg

Phone: +49 6221 54 7322
E-mail: lasse.elsemuellerpsychologie.uni-heidelberg.de
ORCID iD: 0000-0003-0368-720X

Credit: Katrin Glückler

Primary Advisor: Prof. Dr. Andreas Voss (University of Heidelberg)

Additional Supervisors: Stefan Radev (external), Edgar Erdfelder, Andrea Kiesel

Dissertation Proposal: Bridging the Gap between Amortized Bayesian Inference and Cognitive Modeling

Publications
Radev, S. T., Schmitt, M., Schumacher, L., Elsemüller, L., Pratz, V., Schälte, Y., Köthe, U., & Bürkner, P.-C. (2023).
Bayesflow: Amortized bayesian workflows with neural networks. Journal of Open Source Software, 8(89), 5702. https://doi.org/10.21105/joss.05702
Talks
Elsemüller, L., Schnuerch, M., Bürkner, P.-C., & Radev, S. T. (2023, July). Comparing Bayesian hierarchical models: A deep learning method with cognitive applications. Talk presented at the Joint 56th Meeting of the Society for Mathematical Psychology, 21st International Conference on Cognitive Modeling, and 52nd Meeting of the European Mathematical Psychology Group (MathPsych / ICCM / EMPG). Amsterdam, the Netherlands.
Elsemüller, L., Schnuerch, M., Bürkner, P. C., & Radev, S. T. (2023, March). Comparing Bayesian Hierarchical Models of Cognition via Deep Learning. Talk presented at the 65^th Conference of Experimental Psychologists (Tagung experimentell arbeitender Psycholog:innen, TeaP), Trier, Germany.