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Document type:
Masterarbeit 
Author(s):
Johannes Schmitt 
Title:
Interventional Causal Structure Learning With Gaussian Process Regression 
Abstract:
We review the SCM(Structural Causal Model)-view of causal modeling, which features functional dependencies between direct causes and direct effects. In our framework these functions are modeled in the Gaussian Process Regression setting in order to capture nonlinear functions and employ a flexible, non-parametric regression method that works well in the small data setting, which arises when admitting interventions that are assumed to be scarce. Further, we explore how these interventions can be...    »
 
Subject:
MAT Mathematik 
DDC:
510 Mathematik 
Advisor:
Mathias Drton 
Date of acceptation:
15.10.2020 
Year:
2020 
Quarter:
4. Quartal 
Year / month:
2020-10 
Month:
Oct 
Pages:
65 
Language:
en 
University:
Technische Universität München 
Faculty:
Fakultät für Mathematik 
TUM Institution:
Lehrstuhl für Mathematische Statistik 
Format:
Text