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ETH Zurich
A Software Framework for Bayesian Uncertainty Quantification, Optimization, and Reinforcement Learning
Degree
thesis:*- Grantor dc:publisher
- ETH Zurich
- Year dc:date
- 2024
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Wälchli, Daniel Thomas
- Contributors dc:contributor
-
- Katzschmann, Robert K.; id_orcid0000-0001-7143-7259
- Koumoutsakos, Petros
Subjects
dc:subject × 7- Optimization; Uncertainty Quantification; Reinforcement Learning; Inverse reinforcement learning; high performance computing (HPC)
- info:eu-repo/classification/ddc/000
- info:eu-repo/classification/ddc/004
- info:eu-repo/classification/ddc/510
- Generalities, science
- Data processing, computer science
- Mathematics
Rights
dc:rights- Statement dc:rights
-
- info:eu-repo/semantics/openAccess
- In Copyright - Non-Commercial Use Permitted
- Language dc:language
- en
Identifiers
dc:identifier.*- Identifier
- https://doi.org/10.3929/ethz-b-000675461
- OAI identifier oai:identifier
- oai:www.research-collection.ethz.ch:20.500.11850/675461