Active Reinforcement Learning with Monte-Carlo Tree Search. - Sebastian Schulze; Owain Evans (CoRR, 2018)

VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning. - Luisa M. Zintgraf; Kyriacos Shiarlis; Maximilian Igl; Sebastian Schulze; Yarin Gal; Katja Hofmann; Shimon Whiteson (ICLR, 2020)

Bayesian Optimization for Iterative Learning. - Vu Nguyen; Sebastian Schulze; Michael A. Osborne (NeurIPS, 2020)

VariBAD: Variational Bayes-Adaptive Deep RL via Meta-Learning. - Luisa M. Zintgraf; Sebastian Schulze; Cong Lu; Leo Feng; Maximilian Igl; Kyriacos Shiarlis; Yarin Gal; Katja Hofmann; Shimon Whiteson (J. Mach. Learn. Res., 2021)

Marginalising over Stationary Kernels with Bayesian Quadrature. - Saad Hamid; Sebastian Schulze; Michael A. Osborne; Stephen J. Roberts (AISTATS, 2022)

Interpretable Reinforcement Learning via Neural Additive Models for Inventory Management. - Julien Siems; Maximilian Schambach; Sebastian Schulze; Johannes S. Otterbach (CoRR, 2023)

Choose Your Model Size: Any Compression by a Single Gradient Descent. - Martin Genzel; Patrick Putzky; Pengfei Zhao; Sebastian Schulze; Mattes Mollenhauer; Robert Seidel; Stefan Dietzel; Thomas Wollmann (CoRR, 2025)