20 citations · 43 across the 10 of their papers we have counts for
4 papers · 1 filter
Probability trees and the value of a single intervention
Tue Herlau
The most fundamental problem in statistical causality is determining causal relationships from limited data. Probability trees, which combine prior causal structures with Bayesian…
Moral reinforcement learning using actual causation
Tue Herlau
Reinforcement learning systems will to a greater and greater extent make decisions that significantly impact the well-being of humans, and it is therefore essential that these syst…
Active learning of causal probability trees
Tue Herlau
The past two decades have seen a growing interest in combining causal information, commonly represented using causal graphs, with machine learning models. Probability trees provide…
Reinforcement Learning of Causal Variables Using Mediation Analysis
Tue Herlau, Rasmus Larsen
Many open problems in machine learning are intrinsically related to causality, however, the use of causal analysis in machine learning is still in its early stage. Within a general…