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cs.LG2024★ 1 cited
Bayesian Vector AutoRegression with Factorised Granger-Causal Graphs
He Zhao, Vassili Kitsios, Terence J. O'Kane +1
We study the problem of automatically discovering Granger causal relations from observational multivariate time-series data.Vector autoregressive (VAR) models have been time-tested…
cs.LG2024
Permutation-based Inference for Variational Learning of Directed Acyclic Graphs
Edwin V. Bonilla, Pantelis Elinas, He Zhao +3
Estimating the structure of Bayesian networks as directed acyclic graphs (DAGs) from observational data is a fundamental challenge, particularly in causal discovery. Bayesian appro…