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Dinrhiw2

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dinrhiw2

https://github.com/cslr/dinrhiw2
Primary aim of the dinrhiw is to be linear algebra library and machine learning library. For this reason dinrhiw implements PCA and neural network codes. Currently, the neural network code only supports:

  • hamiltonian monte carlo sampling (HMC) and simple bayesian neural network
  • second order L-BFGS search
  • gradient descent (backpropagation)

As well as mathematical routines for arbitrary precision mathematics, hermite curve interpolation and many other things.

Documentation

https://github.com/cslr/dinrhiw2/wiki




Licensing

LicenseVerified byVerified onNotes
GPLv3IanK1 November 2016



Leaders and contributors

Contact(s)Role
Tomas Ukkonen Maintainer/Developer


Resources and communication

Software prerequisites

Kind Description
Required to build blas

This entry (in part or in whole) was last reviewed on 1 November 2016.



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Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.3 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. A copy of the license is included in the page “GNU Free Documentation License”.

The copyright and license notices on this page only apply to the text on this page. Any software or copyright-licenses or other similar notices described in this text has its own copyright notice and license, which can usually be found in the distribution or license text itself.


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