• Maximilian Rixner
  • Markus Schöberl, "Probabilistic Machine Learning Strategies for Coarse-Graining of Molecular Dynamics at Equilibrium” , Ph.D., 2020.
  • Constantin Grigo "Physics-Aware, Bayesian Machine Learning Models for Uncertainty Quantification of High-Dimensional Systems in the Small Data Regime -  Applications in Random Media” , Ph.D., 2020.
  • Isabell Franck, "Sparse Variational Bayesian algorithms for large-scale inverse problems with applications in biomechanics", Ph.D., 2017.