Udo Böhm

Full Name

Dr. U. Böhm

Email

Udo.Boehm@cwi.nl

Room

L133

Department(s)

Machine Learning, Machine Learning

Function(s)

Researcher

Udo Böhm

Ly, A., Böhm, U., & Grünwald, P. (2024). Anytime-valid confidence sequences as a resolution to the Bayesian/frequentist interval debate. Bayesian Analysis, 1–3.
Böhm, U., Evans, N., Gronau, Q., Matzke, D., Wagenmakers, E.-J., & Heathcote, A. (2023). Inclusion Bayes factors for mixed hierarchical diffusion decision models. Psychological Methods. doi:10.1037/met0000582
Böhm, U., Cox, S., Gantner, G., & Stevenson, R. (2022). Efficient numerical approximation of a non-regular Fokker–Planck equation associated with first-passage time distributions. BIT : Numerical Mathematics, 62, 1355–1382. doi:10.1007/s10543-022-00914-2
Böhm, U., Cox, S., Gantner, G., & Stevenson, R. (2021). Fast solutions for the first-passage distribution of diffusion models with space-time-dependent drift functions and time-dependent boundaries. Journal of Mathematical Psychology, 105, 102613:1–102613:12. doi:10.1016/j.jmp.2021.102613
van Doorn, J., van den Bergh, D., Böhm, U., Dablander, F., Derks, K., Draws, T., … Wagenmakers, E.-J. (2021). The JASP guidelines for conducting and reporting a Bayesian analysis. Psychonomic Bulletin & Review, 28, 813–826. doi:10.3758/s13423-020-01798-5