Philip-Bachman

Philip Bachman's repositories

Public repo for Augmented Multiscale Deep InfoMax representation learning

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The useful and used parts of NN-Dropout

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Materials for implementing and reproducing results in the NIPS paper.

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Repo for code for the NIPS paper entitled "An Architecture for Deep, Hierarchical Generative Models"

This code is for training feedforward neural networks with dropout.

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Generative models and other stuff too, maybe, perhaps even probably

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Code for models in my ICML 2015 paper on VAEs, GSNs, etc.

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Code for a variety of approaches to learning classifiers via boosting

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Code for ICML 2014 paper: "Sample-based Approximate Regularization"

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Code for algorithms and tests pertaining to sparse network basis learning

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Assorted code fragments

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Covariance Coding for Image Features

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Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano and TensorFlow.

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Random notes on papers, likely a short-term repo.

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code for performing pragmatic banditry

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