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Probabilistic and Bayesian Modelling II
Published on Feb 25, 20076096 Views
There is a dramatic growth in the availability of complex data from a wide range of different applications. The challenge of the data analyzer is to extract knowledge from the raw data by identifying
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Chapter list
Bayes approach to Linear Regression ...28:28
. . . can be easily generalized to Generalized Linear Models and ....29:42
... to Gaussian Processes32:13
For zero mean, this reads:35:46
Samples from the GP prior40:27
. . . can be easily generalized to Generalized Linear Models and ....41:32
For zero mean, this reads:43:01
Samples from the GP prior43:35
Of course, kernels can be...47:57
Gaussian Process Regression49:36
Samples from the GP posterior57:11
Diagram57:37
Gaussian Process Regression58:56
Predictions & Uncertainty59:05
Gaussian Process Regression01:00:00
Predictions & Uncertainty01:00:23