Temporal latent variable structural causal model for causal discovery under external interferences

Inferring causal relationships from observed data is an important task, yet it becomes challenging when the data is subject to various external interferences. Most of these interferences are the additional effects of external factors on observed variables. Since these external factors are often unkn...

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Veröffentlicht in:	Neurocomputing (Amsterdam) Jg. 640; S. 130281
Hauptverfasser:	Cai, Ruichu, Huang, Xiaokai, Chen, Wei, Li, Zijian, Hao, Zhifeng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.08.2025
Schlagworte:	Causal discovery External interference Latent variables Temporal data Variational inference Latent variables Temporal data Variational inference External interference Causal discovery
ISSN:	0925-2312
Online-Zugang:	Volltext
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