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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
 BibTeX