wolffd@0: wolffd@0: wolffd@0: wolffd@0: Netlab Reference Manual demprior wolffd@0: wolffd@0: wolffd@0: wolffd@0:

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wolffd@0: Purpose wolffd@0:

wolffd@0: Demonstrate sampling from a multi-parameter Gaussian prior. wolffd@0: wolffd@0:

wolffd@0: Synopsis wolffd@0:

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wolffd@0: Description wolffd@0:

wolffd@0: This function plots the functions represented by a multi-layer perceptron wolffd@0: network when the weights are set to values drawn from a Gaussian prior wolffd@0: distribution. The parameters aw1, ab1 aw2 and ab2 wolffd@0: control the inverse variances of the first-layer weights, the hidden unit wolffd@0: biases, the second-layer weights and the output unit biases respectively. wolffd@0: Their values can be adjusted on a logarithmic scale using the sliders, or wolffd@0: by typing values into the text boxes and pressing the return key. wolffd@0: wolffd@0:

wolffd@0: See Also wolffd@0:

wolffd@0: mlp

wolffd@0: Pages: wolffd@0: Index wolffd@0:

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