yangjunpro

1-billion-word-language-modeling-benchmark

Formerly known as code.google.com/p/1-billion-word-language-modeling-benchmark

adaptive-softmax

Implements an efficient softmax approximation as described in the paper "Efficient softmax approximation for GPUs" (http://arxiv.org/abs/1609.04309)

AdversarialNetsPapers

The classical papers and codes about generative adversarial nets

angel

Parameter Server for Spark

ansj_seg

ansj分词.ict的真正java实现.分词效果速度都超过开源版的ict. 中文分词,人名识别,词性标注,用户自定义词典

Arcade-Learning-Environment

The Arcade Learning Environment (ALE) -- a platform for AI research.

arctic-captions

FreeRTB

An experimental system dedicated to Real-Time-Bidding online advertising serving

nnfusion

A flexible and efficient deep neural network (DNN) compiler that generates high-performance executable from a DNN model description.

sling

SLING - A natural language frame semantics parser

yangjunpro/angel

Parameter Server for Spark

yangjunpro/ansj_seg

ansj分词.ict的真正java实现.分词效果速度都超过开源版的ict. 中文分词,人名识别,词性标注,用户自定义词典

yangjunpro/caffe

This fork of BVLC/Caffe is dedicated to improving performance of this deep learning framework when running on CPU, in particular Intel® Xeon processors (HSW+) and Intel® Xeon Phi processors

yangjunpro/CaffeConTroll

yangjunpro/char-rnn

Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch

yangjunpro/convnet-benchmarks

Easy benchmarking of all publicly accessible implementations of convnets

yangjunpro/convnetjs

Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.

yangjunpro/Crepe

Character-level Convolutional Networks for Text Classification

yangjunpro/Deep-Compression-AlexNet

Deep Compression on AlexNet

yangjunpro/deepmark

THE Deep Learning Benchmarks

yangjunpro/fast_rgf

Multi-core implementation of Regularized Greedy Forest

yangjunpro/FasterDNN

Faster Deep Neural Networks

yangjunpro/highwayhash

Fast strong hash functions: SipHash/HighwayHash

yangjunpro/LIBBLE-Spark

yangjunpro/malmo

Project Malmo is a platform for Artificial Intelligence experimentation and research built on top of Minecraft. We aim to inspire a new generation of research into challenging new problems presented by this unique environment.

yangjunpro/maxas

Assembler for NVIDIA Maxwell architecture

yangjunpro/nnvm

Intermediate Computational Graph Representation for Deep Learning Systems

yangjunpro/Omnivore

Omnivore Optimizer and Distributed CcT

yangjunpro/or-tools

Google's Operations Research tools

yangjunpro/P-Multimodal-Dataset-Toolbox

yangjunpro/rnn-benchmarks

Benchmarks for several RNN variations with different deep-learning frameworks

yangjunpro/seq2seq-attn

Sequence-to-sequence model with LSTM encoder/decoders and attention

yangjunpro/seq2seq_chatbot_links

Links to the implementations of neural conversational models for different frameworks

yangjunpro/SeqMatchSeq

yangjunpro/SqueezeNet

SqueezeNet: AlexNet-level accuracy with 50x fewer parameters

yangjunpro/SqueezeNet-Deep-Compression

yangjunpro/stack-lstm-ner

NER system based on stack LSTMs

yangjunpro/tensorflow-1

图解tensorflow 源码

yangjunpro/tinyflow

Tutorial code on how to build your own Deep Learning System in 2k Lines

yangjunpro/vowpal_wabbit

Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.