Bayesian Networks and Causal Discovery

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Open AccessEditorial

by

Xiaoguang Gao

^1,*

and

Zidong Wang

²

¹

School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710129, China

²

Department of Computer Science, City University of Hong Kong, Hong Kong SAR, China

^*

Author to whom correspondence should be addressed.

Entropy 2026, 28(4), 438; https://doi.org/10.3390/e28040438

Submission received: 16 March 2026 / Revised: 31 March 2026 / Accepted: 9 April 2026 / Published: 13 April 2026

(This article belongs to the Special Issue Bayesian Networks and Causal Discovery)

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Excerpt

Note: In lieu of an abstract, this is an excerpt from the first page.

The discovery of the precise causal representations underlying complex data forms
the bedrock of artificial intelligence research [...]

MDPI and ACS Style

Gao, X.; Wang, Z. Bayesian Networks and Causal Discovery. Entropy 2026, 28, 438. https://doi.org/10.3390/e28040438

AMA Style

Gao X, Wang Z. Bayesian Networks and Causal Discovery. Entropy. 2026; 28(4):438. https://doi.org/10.3390/e28040438

Chicago/Turabian Style

Gao, Xiaoguang, and Zidong Wang. 2026. "Bayesian Networks and Causal Discovery" Entropy 28, no. 4: 438. https://doi.org/10.3390/e28040438

APA Style

Gao, X., & Wang, Z. (2026). Bayesian Networks and Causal Discovery. Entropy, 28(4), 438. https://doi.org/10.3390/e28040438

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