vdumoulin github.io

Recent Posts Vincent Dumoulin

Your models in Pylearn2. October 10, 2014. A tutorial on the minimal effort required to develop a new model in Pylearn2. Introducing the VAE framework in Pylearn2. October 08, 2014. Combining variational autoencoders with Not your grandfathers machine learning library. August 28, 2014. Some cool demo I made using a VAE. April 30, 2014. Some more RNN attempts. March 28, 2014. A first attempt at training RNNs. Iterating over variable-length sequences. March 19, 2014. RNNs using the TIMIT dataset. Introd.
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LINKS TO VDUMOULIN.GITHUB.IO

seaandsailor

A really brief introduction to audio signal processing in Julia. Configuring MATLAB to work with XCode 6 on Yosemite. Using stochastic neurons for conditional computation. Using an auditory-inspired representation for speech. Experiments with a 2 layer MLP incorporating phone information. Dictionary Learning and Sparse Coding for Speech Signals.

Representation Learning - ift6266h14 Yoshua Bengios graduate class on representation learning and deep learning

Web site for the graduate class on Representation Learning Algorithms IFT6266 H14.

IFT6266 H2015 Representation Learning A mostly deep learning course

A mostly deep learning course. This is a course on representation learning in general and deep learning in particular. Deep learning has recently been responsible for a large number of impressive empirical gains across a wide array of applications including most dramatically in object recognition and detection in images and speech recognition.

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Recent Posts Vincent Dumoulin

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Your models in Pylearn2. October 10, 2014. A tutorial on the minimal effort required to develop a new model in Pylearn2. Introducing the VAE framework in Pylearn2. October 08, 2014. Combining variational autoencoders with Not your grandfathers machine learning library. August 28, 2014. Some cool demo I made using a VAE. April 30, 2014. Some more RNN attempts. March 28, 2014. A first attempt at training RNNs. Iterating over variable-length sequences. March 19, 2014. RNNs using the TIMIT dataset. Introd.

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The site had the following in the web page, "A tutorial on the minimal effort required to develop a new model in Pylearn2." I observed that the web site stated " Introducing the VAE framework in Pylearn2." They also stated " Combining variational autoencoders with Not your grandfathers machine learning library. Some cool demo I made using a VAE. A first attempt at training RNNs. RNNs using the TIMIT dataset." The meta header had Jekyll as the first keyword. This keyword was followed by theme, responsive, and blog which isn't as important as Jekyll. The other words the site uses is template.

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