56 citations · 144 across the 19 of their papers we have counts for
4 papers · 1 filter
Exact discovery is polynomial for certain sparse causal Bayesian networks
Felix L. Rios, Giusi Moffa, Jack Kuipers
Causal Bayesian networks are widely used tools for summarising the dependencies between variables and elucidating their putative causal relationships. By restricting the search to…
Correcting for confounding in longitudinal experiments: positioning non-linear mixed effects modeling as implementation of standardization using latent conditional exchangeability
Christian Bartels, Martina Scauda, Neva Coello +3
Non-linear mixed effects modeling and simulation (NLME M&S) is evaluated to be used for standardization with longitudinal data in presence of confounders. Standardization is a well…
A new way to evaluate G-Wishart normalising constants via Fourier analysis
Ching Wong, Giusi Moffa, Jack Kuipers
The G-Wishart distribution is a core component for the Bayesian analysis of Gaussian graphical models as the conjugate prior for the precision matrix. Evaluating the marginal likel…
Bayesian Causal Inference with Gaussian Process Networks
Enrico Giudice, Jack Kuipers, Giusi Moffa
Causal discovery and inference from observational data is an essential problem in statistics posing both modeling and computational challenges. These are typically addressed by imp…