Eventstructuremodelsoftenhavesomeconstraintwhichensuresthatforeachsystemrunitisclearwhatarethecausalpredecessorsofanevent(i.e. there is no causal ambiguity). In this contribution w...
We show how a generic feature selection algorithm returning strongly relevant variables can be turned into a causal structure learning algorithm. We prove this under the Faithfuln...
We Imbed Into a first order logic a representation language that combines atemporal knowledge with time stamps in a hierarchical fashion. Each time structure contains its own chro...
Time series prediction is an important issue in a wide range of areas. There are various real world processes whose states vary continuously, and those processes may have influenc...
In time series analysis, inference about causeeffect relationships among multiple times series is commonly based on the concept of Granger causality, which exploits temporal struc...