9494 search results - page 12 / 1899 » Gaussian Process Networks |
ICML
2008
IEEE
14 years 9 months ago
2008
IEEE
Point processes are difficult to analyze because they provide only a sparse and noisy observation of the intensity function driving the process. Gaussian Processes offer an attrac...
ICASSP
2009
IEEE
2009
IEEE
Time-space-sequential algorithms for distributed Bayesian state estimation in serial sensor networks
14 years 3 months ago
We consider distributed estimation of a time-dependent, random state vector based on a generally nonlinear/non-Gaussian state-space model. The current state is sensed by a serial ...
NIPS
2004
13 years 10 months ago
2004
The equivalent kernel [1] is a way of understanding how Gaussian process regression works for large sample sizes based on a continuum limit. In this paper we show (1) how to appro...
ICML
2003
IEEE
14 years 9 months ago
2003
IEEE
We present a novel Bayesian approach to the problem of value function estimation in continuous state spaces. We define a probabilistic generative model for the value function by i...
ICASSP
2009
IEEE
14 years 3 months ago
2009
IEEE
Abstract –In this paper, a variational message passing framework is proposed for Markov random fields, which is computationally more efficient and admits wider applicability comp...