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AAAI
2006
13 years 6 months ago
Mixtures of Predictive Linear Gaussian Models for Nonlinear, Stochastic Dynamical Systems
The Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent parame...
David Wingate, Satinder P. Singh
CEC
2010
IEEE
13 years 8 days ago
Parameter estimation with term-wise decomposition in biochemical network GMA models by hybrid regularized Least Squares-Particle
High-throughput analytical techniques such as nuclear magnetic resonance, protein kinase phosphorylation, and mass spectroscopic methods generate time dense profiles of metabolites...
Prospero C. Naval, Luis G. Sison, Eduardo R. Mendo...
NIPS
2008
13 years 6 months ago
Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes
Identification and comparison of nonlinear dynamical system models using noisy and sparse experimental data is a vital task in many fields, however current methods are computation...
Ben Calderhead, Mark Girolami, Neil D. Lawrence
HYBRID
2000
Springer
13 years 8 months ago
A Dynamic Bayesian Network Approach to Tracking Using Learned Switching Dynamic Models
Abstract. Switching linear dynamic systems (SLDS) attempt to describe a complex nonlinear dynamic system with a succession of linear models indexed by a switching variable. Unfortu...
Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham
GECCO
2005
Springer
180views Optimization» more  GECCO 2005»
13 years 10 months ago
Inference of gene regulatory networks using s-system and differential evolution
In this work we present an improved evolutionary method for inferring S-system model of genetic networks from the time series data of gene expression. We employed Differential Ev...
Nasimul Noman, Hitoshi Iba