60 search results - page 2 / 12 » State-Space Inference and Learning with Gaussian Processes |
ECML
2006
Springer
13 years 9 months ago
2006
Springer
Abstract. In contrast to the standard inductive inference setting of predictive machine learning, in real world learning problems often the test instances are already available at ...
JMLR
2010
13 years 8 days ago
2010
The GPML toolbox provides a wide range of functionality for Gaussian process (GP) inference and prediction. GPs are specified by mean and covariance functions; we offer a library ...
ICML
2009
IEEE
14 years 6 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...
ICASSP
2011
IEEE
12 years 9 months ago
2011
IEEE
We present learning and inference algorithms for a versatile class of partially observed vector autoregressive (VAR) models for multivariate time-series data. VAR models can captu...
ICONIP
2009
13 years 3 months ago
2009
It is generally assumed in the traditional formulation of supervised learning that only the outputs data are uncertain. However, this assumption might be too strong for some learni...