21 search results - page 1 / 5 » Learning Continuous Distributions: Simulations With Field Th... |
NIPS
2000
14 years 15 days ago
2000
Learning of a smooth but nonparametric probability density can be regularized using methods of Quantum Field Theory. We implement a field theoretic prior numerically, test its eff...
ICASSP
2010
IEEE
13 years 9 months ago
2010
IEEE
This paper addresses the problem of state estimation in the case where the prior distribution of the states is not perfectly known but instead is parameterized by some unknown par...
JMLR
2010
13 years 6 months ago
2010
Continuous-time Bayesian networks is a natural structured representation language for multicomponent stochastic processes that evolve continuously over time. Despite the compact r...
ECCV
2006
Springer
15 years 1 months ago
2006
Springer
Abstract. Bayesian inference provides a powerful framework to optimally integrate statistically learned prior knowledge into numerous computer vision algorithms. While the Bayesian...
SIAMIS
2010
13 years 5 months ago
2010
Simulated annealing (SA) and deterministic continuation are well-known generic approaches to global optimization. Deterministic continuation is computationally attractive but produ...