Lasse Elsemüller

According to our database, Lasse Elsemüller authored at least 5 papers between 2023 and 2026.

Collaborative distances:

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

2026

BayesFlow 2.0: Multi-Backend Amortized Bayesian Inference in Python.

Lars Kühmichel, Jerry M. Huang, Valentin Pratz, Jonas Arruda, Hans Olischläger, Daniel Habermann, Simon Kucharský, Lasse Elsemüller, Aayush Mishra, Niels Bracher, Svenja Jedhoff, Marvin Schmitt, Paul-Christian Bürkner, Stefan T. Radev

CoRR, February, 2026

2025

Does Unsupervised Domain Adaptation Improve the Robustness of Amortized Bayesian Inference? A Systematic Evaluation.

Lasse Elsemüller, Valentin Pratz, Mischa von Krause, Andreas Voss, Paul-Christian Bürkner, Stefan T. Radev

Trans. Mach. Learn. Res., 2025

2024

Sensitivity-Aware Amortized Bayesian Inference.

Lasse Elsemüller, Hans Olischläger, Marvin Schmitt, Paul-Christian Bürkner, Ullrich Köthe, Stefan T. Radev

Trans. Mach. Learn. Res., 2024

2023

BayesFlow: Amortized Bayesian Workflows With Neural Networks.

Stefan T. Radev, Marvin Schmitt, Lukas Schumacher, Lasse Elsemüller, Valentin Pratz, Yannik Schälte, Ullrich Köthe, Paul-Christian Bürkner

J. Open Source Softw., October, 2023

A Deep Learning Method for Comparing Bayesian Hierarchical Models.

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

CoRR, 2023