A Software Framework for Bayesian Uncertainty Quantification, Optimization, and Reinforcement Learning
type: CreativeWork
author: Wälchli, Daniel Thomas
language: en
keywords: 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
license: http://rightsstatements.org/page/InC-NC/1.0/
date published: 2024
date modified: 2026-07-27T19:27:16Z
provider: ETH Zürich
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: ETH Zurich

PropertyValue
property ID: Handle
value: http://hdl.handle.net/20.500.11850/675461

PropertyValue
property ID: DOI
value: 10.3929/ethz-b-000675461