Parsimonious Bayesian Deep Networks
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matlab_functions
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DNN_Table1.py
DNN_all.py
Demo_PBDN_GibbsSampling.m
Demo_PBDN_TwoSpirals.m
LICENSE
PBDN_MAP_SGD.py
README.md
Two_spirials_PBDN_1to10layers.gif

README.md

PBDN

Parsimonious Bayesian Deep Networks

Code for

    @inproceedings{Zhou_PBDN_2018,      
            Author = {Mingyuan Zhou},
            Booktitle = {NIPS},
            Title = {Parsimonious Bayesian Deep Networks},	
            Year = {2014}
    }

Python (TensorFlow) code is for MAP inference via SGD

Matlab code is for Bayesian inference via Gibbs sampling

PBDN_MAP_SGD.py: reproduce the results of PBDN with SGD based MAP inference in Tables 1-3 and 5

Demo_PBDN_GibbsSampling.m: reproduce the results of PBDN with Gibbs sampling in Tables 2, 3, and 5

Demo_PBDN_TwoSpirals.m: reproduce Figure 1