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MMAS
2011
Springer
13 years 2 months ago
Scalable Bayesian Reduced-Order Models for Simulating High-Dimensional Multiscale Dynamical Systems
While existing mathematical descriptions can accurately account for phenomena at microscopic scales (e.g. molecular dynamics), these are often high-dimensional, stochastic and thei...
Phaedon-Stelios Koutsourelakis, Elias Bilionis
BIOSYSTEMS
2008
100views more  BIOSYSTEMS 2008»
13 years 7 months ago
Objective patterns in the evolving network of non-equivalent observers
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...
Abir U. Igamberdiev
METMBS
2003
255views Mathematics» more  METMBS 2003»
13 years 9 months ago
Causal Explorer: A Causal Probabilistic Network Learning Toolkit for Biomedical Discovery
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...
ICML
2006
IEEE
14 years 8 months ago
Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems
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...
David Wingate, Satinder P. Singh
FORMATS
2005
Springer
14 years 1 months ago
Time Supervision of Concurrent Systems Using Symbolic Unfoldings of Time Petri Nets
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...
Thomas Chatain, Claude Jard