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My Notes on Deep Belief NetworksI think the Deep Belief Networks of Hinton et al are quite interesting.. in that they are real science with measurable results that has been reproduced by multiple implementations. The 2006 paper that started it all and Hinton's presentation on google video: http://www.gatsby.ucl.ac.uk/~ywteh/research/ebm/nc2006.pdfhttp://video.google.com.au/videoplay?docid=228784531481853811 A formal analysis: http://www.cs.utoronto.ca/~ilya/pubs/2007/inf_deep_net_utml.pdfApplication to natural language processing: http://www.cs.swarthmore.edu/~meeden/cs81/s08/DahlLaTouche.pdfhttp://www.machinelearning.org/proceedings/icml2007/papers/425.pdf Reproducing Hinton and extension to and evaluation in other domains: http://www.machinelearning.org/proceedings/icml2007/papers/331.pdfUse in Computer animation of facial expressions: http://aclab.ca/users/josh/downloads/pubs/23_Susskind_Hinton_Movellan_Anderson.pdfMost impressive: http://www.cs.utoronto.ca/~ilya/pubs/2007/aistats_multilayered.pdfA C++ implementation (although it has much Python love): http://plearn.berlios.de/A Java implementation: http://www.sourceforge.net/projects/jarbmSo yeah, there's some pretty good demonstrations of how powerful DBNs are.. QuantumG<< back to my home page Anonymous says: Interesting notes... I read "On Intelligence" and enjoyed greatly the ideas. Last I checked, Numenta hasn't implemented what's discussed in the book yet, though. Maybe when they get there it will be more interesting. You mention jaRBM: I'm trying to find a Java DBN impl. jaRBM does RBM, does it do DBN? I didn't see DBN mentioned in the code. Maybe its by a different name. |