In scientific inference problems, the underlying statistical modeling
as...
We present the particle stochastic approximation EM (PSAEM) algorithm fo...
The choice of model class is fundamental in statistical learning and sys...
The choice of model class is fundamental in statistical learning and sys...
When classical particle filtering algorithms are used for maximum likeli...
Probabilistic (or Bayesian) modeling and learning offers interesting
pos...
We consider a nonlinear state-space model with the state transition and
...
Gaussian processes allow for flexible specification of prior assumptions...
One of the key challenges in identifying nonlinear and possibly non-Gaus...
Gaussian process regression is a popular method for non-parametric
proba...
Jump Markov linear models consists of a finite number of linear state sp...