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165
Voted
SIAMIS
2011
14 years 10 months ago
2011
Abstract. Many problems of low-level computer vision and image processing, such as denoising, deconvolution, tomographic reconstruction or superresolution, can be addressed by maxi...
145
Voted
ICML
2008
IEEE
16 years 4 months ago
2008
IEEE
Stationarity is often an unrealistic prior assumption for Gaussian process regression. One solution is to predefine an explicit nonstationary covariance function, but such covaria...
133
Voted
SAC
2008
ACM
15 years 3 months ago
2008
ACM
For short-term forecasting of wind generation, a necessary step is to model the function for the conversion of meteorological variables (mainly wind speed) to power production. Su...
148
Voted
ICML
2008
IEEE
16 years 4 months ago
2008
IEEE
Most existing sparse Gaussian process (g.p.) models seek computational advantages by basing their computations on a set of m basis functions that are the covariance function of th...
169
Voted
NIPS
2008
15 years 5 months ago
2008
Identification and comparison of nonlinear dynamical system models using noisy and sparse experimental data is a vital task in many fields, however current methods are computation...