Scientific Talks and Posters

Below you can find a list of selected talks and posters of me and my group, along with slides, paper references, and recordings when available. Presenters are highlighted in bold.

• Bockting F., Radev S. T., & Bürkner P. C. (2024). Invited talk: Simulation-Based Prior Knowledge Elicitation for Parametric Bayesian Models. Presented at Bayes@Lund. Slides Youtube Paper

• Bürkner P. C. (2024). Keynote: Does Bayes have to be slow? A glimpse into amortized Bayesian inference. Presented at Bayes on the Beach. Slides Paper Software

• Schmitt M. & Bürkner P. C. (2024). Workshop: Amortized Bayesian Inference with BayesFlow. Presented at Bayes on the Beach. Notebook Software

• Bürkner P. C. (2023). Keynote: Bayesian Probabilistic Modeling for Ecology. Presented at Oxford University. Slides

• Bürkner P. C. (2023). Invited talk: Testing evidence of absence with Bayesian methods. Presented at University of Tübingen. Slides

• Bürkner P. C. (2023). Invited talk: Best Practices for Supervision of Bachelor’s and Master’s Students. Presented at the International Max Planck Research School for Intelligent Systems. Slides

• Aguilar J. E. & Bürkner P. C. (2023). Poster: Intuitive Joint Priors for Bayesian Multilevel Models: The R2D2M2 Prior. Presented at BayesComp. Slides Paper

• Schmitt, M., Radev, S. T., & Bürkner, P. C. (2023). Poster: Meta-Uncertainty in Bayesian Model Comparison. Presented at AISTATS. Slides Paper

• Schmitt, M., Bürkner, P. C., Köthe, U., & Radev, S. T. (2023). Talk: Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks. Presented at the German Conference on Pattern Recognition. Slides Poster Paper

• Schmitt, M., Habermann, D., Bürkner, P. C., & Radev, S. T. (2023). Talk: Leveraging Self-Consistency for Data-Efficient Amortized Bayesian Inference. Presented at the NeurIPS Workshop for Unifying Representations in Neural Models. Slides Paper

• Scholz M. & Bürkner P.C. (2023). Talk: Prediction can be safely used as a proxy for explanation in causally consistent Bayesian GLMs. Presented at Nordstat. Slides Paper

• Bürkner P. C., Kröker I., Oladyshkin S., & Nowak W. (2022). Talk: The Sparse Bayesian Polynomial Chaos Expansion. Presented at the DagStat Conference. Slides Paper

• Aguilar J. E. & Bürkner P. C. (2022). Talk: Intuitive Joint Priors for Bayesian Multilevel Models Presented at the International Conference on Statistics and Data Science. Slides Paper

• Bürkner P. C. (2022). Invited talk: Probabilistic Learning Theory. Presented at the Stuttgart ELLIS unit. Slides Youtube

• Bürkner P. C. (2022). Invited talk: Measuring Personality in High-Stakes Situations. Presented at the Interchange Forum for Reflecting on Intelligent Systems. Slides Paper

• Bürkner P. C. (2021). Keynote: Bayesian Item Response Modeling in R with brms and Stan. Presented at the Psychoco Conference. Slides Youtube Paper

• Bürkner P. C. (2021). Invited talk: Specifying Priors in a Bayesian Workflow. Presented at the Berlin Bayesian Meetup. Slides Youtube

• Bürkner P. C. (2021). Keynote: An introduction to Bayesian multilevel modeling with brms. Presented at the Multilevel Conference. Slides Youtube Paper

• Bürkner P. C. (2021). Invited talk: Bayesian distributional regression models for cognitive science. Presented at TU Darmstadt University. Slides

• Bürkner P. C. (2021). Invited talk: Introduction to Bayesian Statistics. Presented at the Cluster of Excellence SimTech. Slides

• Bürkner P. C. (2021). Invited talk: The Past, Present & Future of brms. Presented on learnbayesstats.com. Potcast Youtube Software

• Bürkner P. C. (2020). Keynote: A Bayesian Workflow for Data Analysis. Presented at the Summer School on Statistical Methods for Linguistics and Psychology. Slides Paper

• Vehtari A., Gelman A., Simpson D., Carpenter B., Bürkner P. C. (2020). Talk: Improving Convergence Diagnostics for MCMC Sampling Algorithms. Presented at the DGPs Methods Conference. Slides Paper

• Bürkner P. C., Gabry J., & Vehtari A. (2019). Talk: Approximate leave-future-out cross-validation for Bayesian time series models. Presented at StanCon. Slides Youtube Paper

• Bürkner P. C. & Charpentier E. (2019). Talk: Modeling Monotonic Effects of Ordinal Predictors in Regression Models. Presented at the EAM Conference. Slides Paper

• Bürkner P. C. (2019). Invited talk: Bayesian model and variable selection using approximate cross-validation and projective predictions. Presented at Imperial College London. Slides

• Bürkner P. C. (2018). Talk: Custom Response Distributions with brms. Presented at StanCon. Slides Youtube Software

• Bürkner P. C. (2018). Invited talk: From Classical GLMs to Bayesian MLMs. Presented at Insurance Data Science Conference. Slides

• Bürkner P. C. (2018). Invited talk: Bayesian Cognitive Models. Presented at the University of Magdeburg. Slides

• Bürkner P. C. (2017). Invited talk: Optimal Design and Bayesian Data Analysis. Presented at the DGPs Methods Conference. Slides

• Bürkner P. C. (2015). Talk: Optimal Design of Non-Parametric Two-Sample Tests. Presented at the DGPs Methods Conference. Slides Paper