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Sebastian Schulze
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2020 – today
- 2023
- [i5]Julien Siems, Maximilian Schambach
, Sebastian Schulze, Johannes S. Otterbach:
Interpretable Reinforcement Learning via Neural Additive Models for Inventory Management. CoRR abs/2303.10382 (2023) - 2022
- [c3]Saad Hamid, Sebastian Schulze, Michael A. Osborne, Stephen J. Roberts:
Marginalising over Stationary Kernels with Bayesian Quadrature. AISTATS 2022: 9776-9792 - 2021
- [j1]Luisa M. Zintgraf, Sebastian Schulze, Cong Lu, Leo Feng, Maximilian Igl, Kyriacos Shiarlis, Yarin Gal, Katja Hofmann, Shimon Whiteson:
VariBAD: Variational Bayes-Adaptive Deep RL via Meta-Learning. J. Mach. Learn. Res. 22: 289:1-289:39 (2021) - [i4]Saad Hamid, Sebastian Schulze, Michael A. Osborne, Stephen J. Roberts:
Marginalising over Stationary Kernels with Bayesian Quadrature. CoRR abs/2106.07452 (2021) - 2020
- [c2]Luisa M. Zintgraf, Kyriacos Shiarlis, Maximilian Igl, Sebastian Schulze, Yarin Gal, Katja Hofmann, Shimon Whiteson:
VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning. ICLR 2020 - [c1]Vu Nguyen, Sebastian Schulze, Michael A. Osborne:
Bayesian Optimization for Iterative Learning. NeurIPS 2020
2010 – 2019
- 2019
- [i3]Vu Nguyen, Sebastian Schulze, Michael A. Osborne:
Bayesian Optimization for Iterative Learning. CoRR abs/1909.09593 (2019) - [i2]Luisa M. Zintgraf, Kyriacos Shiarlis, Maximilian Igl, Sebastian Schulze, Yarin Gal, Katja Hofmann, Shimon Whiteson:
VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning. CoRR abs/1910.08348 (2019) - 2018
- [i1]Sebastian Schulze, Owain Evans:
Active Reinforcement Learning with Monte-Carlo Tree Search. CoRR abs/1803.04926 (2018)
Coauthor Index
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