107 search results - page 1 / 22 » Fast Gaussian process methods for point process intensity es... |
ICML
2008
IEEE
14 years 5 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...
NIPS
2004
13 years 6 months ago
2004
Log-concavity is an important property in the context of optimization, Laplace approximation, and sampling; Bayesian methods based on Gaussian process priors have become quite pop...
ICML
2009
IEEE
14 years 5 months ago
2009
IEEE
The inhomogeneous Poisson process is a point process that has varying intensity across its domain (usually time or space). For nonparametric Bayesian modeling, the Gaussian proces...
WSC
2008
13 years 7 months ago
2008
Point processes with stochastic intensities are ubiquitous in many application areas, including finance, insurance, reliability and queuing. They can be simulated from standard Po...
NIPS
2008
13 years 6 months ago
2008
Learning in real-time applications, e.g., online approximation of the inverse dynamics model for model-based robot control, requires fast online regression techniques. Inspired by...