Stefan T. Radev

According to our database, Stefan T. Radev authored at least 9 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2023

A Deep Learning Method for Comparing Bayesian Hierarchical Models.

Lasse Elsemüller, Martin Schnuerch, Paul-Christian Bürkner, Stefan T. Radev

CoRR, 2023

2022

BayesFlow: Learning Complex Stochastic Models With Invertible Neural Networks.

Stefan T. Radev, Ulf K. Mertens, Andreas Voss, Lynton Ardizzone, Ullrich Köthe

IEEE Trans. Neural Networks Learn. Syst., 2022

Meta-Uncertainty in Bayesian Model Comparison.

Marvin Schmitt, Stefan T. Radev, Paul-Christian Bürkner

CoRR, 2022

2021

Deep Learning Architectures for Amortized Bayesian Inference in Cognitive Modeling.

Stefan T. Radev

PhD thesis, 2021

OutbreakFlow: Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks and its application to the COVID-19 pandemics in Germany.

Stefan T. Radev, Frederik Graw, Simiao Chen, Nico T. Mutters, Vanessa Eichel, Till Bärnighausen, Ullrich Köthe

PLoS Comput. Biol., 2021

BayesFlow can reliably detect Model Misspecification and Posterior Errors in Amortized Bayesian Inference.

Marvin Schmitt, Paul-Christian Bürkner, Ullrich Köthe, Stefan T. Radev

CoRR, 2021

2020

Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks.

Stefan T. Radev, Frederik Graw, Simiao Chen, Nico T. Mutters, Vanessa Eichel, Till Bärnighausen, Ullrich Köthe

CoRR, 2020

Amortized Bayesian Inference for Models of Cognition.

Stefan T. Radev, Andreas Voss, Eva Marie Wieschen, Paul-Christian Bürkner

CoRR, 2020

Amortized Bayesian model comparison with evidential deep learning.

Stefan T. Radev, Marco D'Alessandro, Paul-Christian Bürkner, Ulf K. Mertens, Andreas Voss, Ullrich Köthe

CoRR, 2020