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Crino: a neural-network library based on Theano
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Added `NegativeLogLikelihood` class as a new criterion for multi-clas…

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Julien Lerouge authored

README.md

Crino: a neural-network library based on Theano

Crino is an open-source Python library aimed at building and training artificial neural-networks. It has been developed on top of Theano, by researchers from the LITIS laboratory.

Crino lets you "hand-craft" neural-network architectures, using a modular framework inspired by Torch. Our library also provides standard implementations for :

  • auto-encoders (AE)
  • multi-layer perceptrons (MLP)
  • deep neural networks (DNN)
  • input-output deep architectures (IODA)

IODA

IODA is a specialization of the DNNs, specifically designed for cases where you have to deal with high-dimensional input and output spaces. The input and output layers are initialized with an unsupervised pre-training step. Then, the backpropagation algorithm performs the supervised learning final step. This process is based on the stacked auto-encoder strategy, commonly used by DNN training algorithms.

We are currently writing an article on IODA, we'll inform you as soon as it is ready to publish.

Getting started

  • Install Crino :
cd to/your/preferred/path
git clone https://github.com/jlerouge/crino.git
cd crino
sudo python setup.py install
  • Run the given example :
cd example
chmod +x example.py
./example.py
  • Adapt it to your needs! Crino is natively compatible with Matlab-like data or any format handled by SciPy/NumPy.
  • Check the project documentation

FAQ

Contact

You can contact us with the following e-mail address : crino-contact@litislab.fr.

Feel free to open a new issue in case you have found a bug in Crino.

Credits

Crino is based on Theano :

  • J. Bergstra, O. Breuleux, F. Bastien, P. Lamblin, R. Pascanu, G. Desjardins, J. Turian, D. Warde-Farley and Y. Bengio. “Theano: A CPU and GPU Math Expression Compiler”. Proceedings of the Python for Scientific Computing Conference (SciPy) 2010. June 30 - July 3, Austin, TX

IODA is based on B. Labbé's et al. work :

Disclaimer

Copyright (c) 2014 Clément Chatelain, Romain Hérault, Julien Lerouge, Romain Modzelewski (LITIS - EA 4108).

All rights reserved.

This program is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details.

The sample data (located in example/data) are free of use.

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