Looks like it's here: https://github.com/ghubber/boltzmann
Christopher Small <mailto:metasoar...@gmail.com>
January 4, 2015 at 6:45 PM
Where is the repository?
On Sunday, January 4, 2015 4:07:22 PM UTC-7, Christian Weilbach wrote:
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Christian Weilbach <mailto:whitesp...@polyc0l0r.net>
January 4, 2015 at 4:07 PM
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Hi all,
- From the README:
This library is supposed to implement Boltzmann Machines, Autoencoders
and related deep learning technologies. All implementations should
both have a clean high-level mathematical implementation of their
algorithms (with core.matrix) and if possible, an optimized and
benchmarked version of the core routines for production use. This is
to facilitate learning for new users or potential contributors, to be
able to implement algorithms from papers/other languages and then tune
them for performance if needed.
This repository is supposed to cover techniques building on Restricted
Boltzmann Machines, like Deep Belief Networks, Deep Boltzmann Machines
or temporal extensions thereof as well as Autoencoders (which I am not
familiar enough with yet). Classical back-propagation is also often
used to fine-tune deep models supervisedly, so networks should support
it as well.
I haven't build myself deep belief networks out of it yet, but this
should be fairly straightforward. Also combination with the usual
linear classifiers (logistic regression, SVM) at the top layer can be
explored. If somebody has interest/experience in/with implementing
standard backpropagation, go ahead and open a pull-request :-).
Christian
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