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ESANN
2006
15 years 6 months ago
A Gaussian process latent variable model formulation of canonical correlation analysis
Abstract. We investigate a nonparametric model with which to visualize the relationship between two datasets. We base our model on Gaussian Process Latent Variable Models (GPLVM)[1...
Gayle Leen, Colin Fyfe
110
Voted
NIPS
2001
15 years 6 months ago
A Bayesian Model Predicts Human Parse Preference and Reading Times in Sentence Processing
Narayanan and Jurafsky (1998) proposed that human language comprehension can be modeled by treating human comprehenders as Bayesian reasoners, and modeling the comprehension proce...
S. Narayanan, Daniel Jurafsky
DMSN
2007
ACM
15 years 8 months ago
Declarative temporal data models for sensor-driven query processing
Many sensor network applications monitor continuous phenomena by sampling, and fit time-varying models that capture the phenomena's behaviors. We introduce Pulse, a framework...
Yanif Ahmad, Ugur Çetintemel
IROS
2008
IEEE
211views Robotics» more  IROS 2008»
15 years 11 months ago
GP-BayesFilters: Bayesian filtering using Gaussian process prediction and observation models
Abstract— Bayesian filtering is a general framework for recursively estimating the state of a dynamical system. The most common instantiations of Bayes filters are Kalman filt...
Jonathan Ko, Dieter Fox
122
Voted
DAC
2006
ACM
16 years 5 months ago
Process variation aware OPC with variational lithography modeling
Optical proximity correction (OPC) is one of the most widely used resolution enhancement techniques (RET) in nanometer designs to improve subwavelength printability. Conventional ...
Peng Yu, Sean X. Shi, David Z. Pan