Learning latent functions for causal discovery

Learning latent functions for causal discovery

Causal discovery from observational data offers unique opportunities in many scientific disciplines: reconstructing causal drivers, testing causal hypotheses, and comparing and evaluating models for optimizing targeted interventions. Recent causal discovery methods focused on estimating the latent s...

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Bibliographic Details
Main Authors: Emiliano Díaz, Gherardo Varando, J Emmanuel Johnson, Gustau Camps-Valls
Format: Article
Language:English
Published: IOP Publishing 2023-01-01
Series:Machine Learning: Science and Technology
Subjects:
causal inference
causal discovery
additivity
kernel methods
latent variables
causal sufficiency
Online Access:https://doi.org/10.1088/2632-2153/ace151

Internet

https://doi.org/10.1088/2632-2153/ace151

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