Variational methods for simulation-based inference. - Manuel Glöckler; Michael Deistler; Jakob H. Macke (ICLR, 2022)

NCMW: A Python Package to Analyze Metabolic Interactions in the Nasal Microbiome. - Manuel Glöckler; Andreas Dräger; Reihaneh Mostolizadeh (Frontiers Bioinform., 2022)

Adversarial robustness of amortized Bayesian inference. - Manuel Glöckler; Michael Deistler; Jakob H. Macke (ICML, 2023)

Hierarchical modelling of microbial communities. - Manuel Glöckler; Andreas Dräger; Reihaneh Mostolizadeh (Bioinform., 2023)

All-in-one simulation-based inference. - Manuel Glöckler; Michael Deistler; Christian Dietrich Weilbach; Frank Wood; Jakob H. Macke (ICML, 2024)

Inferring stochastic low-rank recurrent neural networks from neural data. - Matthijs Pals; A Erdem Sagtekin; Felix Pei; Manuel Glöckler; Jakob H. Macke (NeurIPS, 2024)

A Practical Guide to Statistical Distances for Evaluating Generative Models in Science. - Sebastian Bischoff 001; Alana Darcher; Michael Deistler; Richard Gao; Franziska Gerken; Manuel Glöckler; Lisa Haxel; Jaivardhan Kapoor; Janne K. Lappalainen; Jakob H. Macke; Guy Moss 001; Matthijs Pals; et al. (CoRR, 2024)

A Practical Guide to Sample-based Statistical Distances for Evaluating Generative Models in Science. - Sebastian Bischoff 001; Alana Darcher; Michael Deistler; Richard Gao; Franziska Gerken; Manuel Glöckler; Lisa Haxel; Jaivardhan Kapoor; Janne K. Lappalainen; Jakob H. Macke; Guy Moss 001; Matthijs Pals; et al. (Trans. Mach. Learn. Res., 2024)

Compositional simulation-based inference for time series. - Manuel Glöckler; Shoji Toyota; Kenji Fukumizu; Jakob H. Macke (ICLR, 2025)

Effortless, Simulation-Efficient Bayesian Inference using Tabular Foundation Models. - Julius Vetter; Manuel Glöckler; Daniel Gedon; Jakob H. Macke (CoRR, 2025)

sbi reloaded: a toolkit for simulation-based inference workflows. - Jan Boelts; Michael Deistler; Manuel Glöckler; Álvaro Tejero-Cantero; Jan-Matthis Lueckmann; Guy Moss 001; Peter Steinbach; Thomas Moreau 001; Fabio Muratore; Julia Linhart; Conor Durkan; Julius Vetter; et al. (J. Open Source Softw., 2025)