While existing mathematical descriptions can accurately account for phenomena at microscopic scales (e.g. molecular dynamics), these are often high-dimensional, stochastic and thei...
The world's objective pattern is formed through consistent histories of quantum measurements originating as different branches of the same wave function. When we come close t...
Causal Probabilistic Networks (CPNs), (a.k.a. Bayesian Networks, or Belief Networks) are well-established representations in biomedical applications such as decision support system...
Constantin F. Aliferis, Ioannis Tsamardinos, Alexa...
The recent Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent...
Monitoring real-time concurrent systems is a challenging task. In this paper we formulate (model-based) supervision by means of hidden state history reconstruction, from event (e.g...