2 citations · 6 across the 12 of their papers we have counts for
3 papers · 1 filter
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…
Fair Clustering: A Causal Perspective
Fritz Bayer, Drago Plecko, Niko Beerenwinkel +1
Clustering algorithms may unintentionally propagate or intensify existing disparities, leading to unfair representations or biased decision-making. Current fair clustering methods…
A Bayesian Take on Gaussian Process Networks
Enrico Giudice, Jack Kuipers, Giusi Moffa
Gaussian Process Networks (GPNs) are a class of directed graphical models which employ Gaussian processes as priors for the conditional expectation of each variable given its paren…