1 citations · 1 across the 4 of their papers we have counts for
4 papers
Time series causal discovery with variable lags
Bruno Petrungaro, Anthony C. Constantinou
Causal Bayesian Networks (CBNs) are a powerful tool for reasoning under uncertainty about complex real-world problems. Such problems evolve over time, responding to external shocks…
Econometric vs. Causal Structure-Learning for Time-Series Policy Decisions: Evidence from the UK COVID-19 Policies
Bruno Petrungaro, Anthony C. Constantinou
Causal machine learning (ML) recovers graphical structures that inform us about potential cause-and-effect relationships. Most progress has focused on cross-sectional data with no…
Investigating potential causes of Sepsis with Bayesian network structure learning
Bruno Petrungaro, Neville K. Kitson, Anthony C. Constantinou
Sepsis is a life-threatening and serious global health issue. This study combines knowledge with available hospital data to investigate the potential causes of Sepsis that can be a…
Open problems in causal structure learning: A case study of COVID-19 in the UK
Anthony Constantinou, Neville K. Kitson, Yang Liu +5
Causal machine learning (ML) algorithms recover graphical structures that tell us something about cause-and-effect relationships. The causal representation praovided by these algor…