Deep recurrent modelling of Granger causality with latent confounding

Author:

Yin ZexuanORCID,Barucca PaoloORCID

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference33 articles.

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3. Time series deconfounder: Estimating treatment effects over time in the presence of hidden confounders;Bica,2020

4. Neural additive vector autoregression models for causal discovery in time series data;Bussmann,2020

5. Frequency decomposition of conditional Granger causality and application to multivariate neural field potential data;Chen;Journal of Neuroscience Methods,2006

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