Neural Posterior Domain Randomization. - Fabio Muratore; Theo Gruner; Florian Wiese; Boris Belousov; Michael Gienger; Jan Peters 001 (CoRL, 2021)

Pseudo-Likelihood Inference. - Theo Gruner; Boris Belousov; Fabio Muratore; Daniel Palenicek; Jan R. Peters (NeurIPS, 2023)

Learning Tactile Insertion in the Real World. - Daniel Palenicek; Theo Gruner; Tim Schneider; Alina Böhm; Janis Lenz; Inga Pfenning; Eric Krämer; Jan Peters 001 (CoRR, 2024)

Analysing the Interplay of Vision and Touch for Dexterous Insertion Tasks. - Janis Lenz; Theo Gruner; Daniel Palenicek; Tim Schneider; Jan Peters 001 (CoRR, 2024)

Machine Learning with Physics Knowledge for Prediction: A Survey. - Joe Watson; Chen Song; Oliver Weeger; Theo Gruner; An Thai Le 001; Kay Hansel; Ahmed Hendawy; Oleg Arenz; Will Trojak; Miles D. Cranmer; Carlo D'Eramo; Fabian Bülow; et al. (Trans. Mach. Learn. Res., 2025)

Towards Safe Robot Foundation Models. - Maximilian Tölle; Theo Gruner; Daniel Palenicek; Jonas Günster; Puze Liu; Joe Watson; Davide Tateo; Jan Peters 001 (CoRR, 2025)

Towards Safe Robot Foundation Models Using Inductive Biases. - Maximilian Tölle; Theo Gruner; Daniel Palenicek; Tim Schneider; Jonas Günster; Joe Watson; Davide Tateo; Puze Liu; Jan Peters 001 (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)