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Korali: Efficient and Scalable Software Framework for Bayesian
  Uncertainty Quantification and Stochastic Optimization

Korali: Efficient and Scalable Software Framework for Bayesian Uncertainty Quantification and Stochastic Optimization

27 May 2020
Sergio M. Martin
Daniel Wälchli
G. Arampatzis
Athena Economides
Petr Karnakov
Petros Koumoutsakos
ArXivPDFHTML

Papers citing "Korali: Efficient and Scalable Software Framework for Bayesian Uncertainty Quantification and Stochastic Optimization"

1 / 1 papers shown
Title
Discovering Individual Rewards in Collective Behavior through Inverse
  Multi-Agent Reinforcement Learning
Discovering Individual Rewards in Collective Behavior through Inverse Multi-Agent Reinforcement Learning
Daniel Waelchli
Pascal Weber
Petros Koumoutsakos
AI4CE
27
4
0
17 May 2023
1