Pinned Repositories
adasecant_wshp_paper
Code for the arxiv paper
Arcade-Universe
Arcade Dataset Generator
Attentive_reader
Simple Attentive Reader Code
autoencoders
Implementation of several different types of autoencoders
dntm
D-NTM paper repo
gitsh
A simple git shell
jDenetX
Java Based Traffic Classifier
noisy_units
Codes for the "Noisy Activation Functions" paper.
pointer_softmax
simple_regex
A simple Regular expression matcher
caglar's Repositories
caglar/prmlp
prmlp
caglar/kmatters
Knowledge Matters Paper References
caglar/PowerupAE
PowerupAE
caglar/bugland
Dataset generator
caglar/DeepLearningBenchmarks
caglar/experimentations
algorithm experimentations
caglar/GeometricShapeGenerator
Geometric Shape Generator
caglar/HilbertCurves
caglar/ift6266-project
Ift6266 project report
caglar/pylearn_old
A Machine Learning library based on Theano
caglar/Bios366
Advanced Statistical Computing at Vanderbilt University's Department of Biostatistics
caglar/brown-cluster
C++ implementation of the Brown word clustering algorithm.
caglar/carray
A chunked data container that can be compressed in-memory.
caglar/cascaded_ensembles
Cascaded ensembles for pylearn2
caglar/ContestDataset
A Pylearn2 Dataset object for accessing the dataset used for the kaggle competition of IFT 6266 H13
caglar/Damian-Conway-s-Vim-Setup
caglar/gfx.js
A graphics backend for the browser (with a Torch7 client).
caglar/gitignores
My gitignore files
caglar/glances
Glances an Eye on your system
caglar/GroundHog
Library for implementing RNNs with Theano
caglar/lualint
lua linter
caglar/matplotlibrc
some example matplotlibrc files, and a script display their effects
caglar/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
An introduction to Bayesian methods + probabilistic programming in data analysis with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
caglar/pylearn2
A Machine Learning library based on Theano
caglar/spearmint
Spearmint is a package to perform Bayesian optimization according to the algorithms outlined in the paper: Practical Bayesian Optimization of Machine Learning Algorithms. Jasper Snoek, Hugo Larochelle and Ryan P. Adams. Advances in Neural Information Processing Systems, 2012
caglar/structured_mlp
Basic source code of the structured MLP used in the ICLR 2013 submission
caglar/tmux-config
Example tmux configuration - screen + vim key-bindings, system stat, cpu load bar.
caglar/torch7-distro
Torch7: state-of-the-art machine learning algorithms
caglar/vimified
Kick-ass Vim configuration framework.
caglar/writegood.vim
Vim plugin for Matt Might's '3 shell scripts that can improve your writing'