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NIPS
2003
15 years 7 months ago
Gaussian Process Latent Variable Models for Visualisation of High Dimensional Data
In this paper we introduce a new underlying probabilistic model for principal component analysis (PCA). Our formulation interprets PCA as a particular Gaussian process prior on a ...
Neil D. Lawrence
GRAPHICSINTERFACE
1996
15 years 7 months ago
Rendering Caustics on Non-Lambertian Surfaces
This paper presents a new technique for rendering caustics on non-Lambertian surfaces. The method is based on an extension of the photon map which removes previous restrictions li...
Henrik Wann Jensen
DASFAA
2010
IEEE
191views Database» more  DASFAA 2010»
15 years 6 months ago
Answering Top-k Similar Region Queries
Abstract. Advances in web technology have given rise to new information retrieval applications. In this paper, we present a model for geographical region search and call this class...
Chang Sheng, Yu Zheng, Wynne Hsu, Mong-Li Lee, Xin...
CVIU
2007
154views more  CVIU 2007»
15 years 6 months ago
Bayesian stereo matching
A Bayesian framework is proposed for stereo vision where solutions to both the model parameters and the disparity map are posed in terms of predictions of latent variables, given ...
Li Cheng, Terry Caelli
NECO
2002
104views more  NECO 2002»
15 years 6 months ago
An Unsupervised Ensemble Learning Method for Nonlinear Dynamic State-Space Models
A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
Harri Valpola, Juha Karhunen