Weekly Machine Learning Opensource Roundup – Dec. 7, 2017

Examples

Stanford DAWNBench
An End-to-End Deep Learning Benchmark and Competition

Neural Network in JavaScript with Deeplearn.js
Using a Neural Network to choose a accessible font color based on a background color.

Cat Classifier
An experiment to visualize a trained deep neural network as activation plots

TSNE Embedding Visualisation
A Simple and easy to use way to Visualise Embeddings!

Toolsets

OpenAI Blocksparse
Efficient GPU kernels for block-sparse matrix multiplication and convolution

Stream Reactor
Streaming reference architecture for ETL with Kafka and Kafka-Connect

CALDERA
An automated adversary emulation system

MatchZoo
MatchZoo is a toolkit for text matching. It was developed to facilitate the designing, comparing, and sharing of deep text matching models.

Google DeepVariant
An analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.

HoME Platform
A Household Multimodal Environment is a platform for artificial agents to learn from vision, audio, semantics, physics, and interaction with objects and other agents, all within a realistic context.

Models

CNN-DCNN text autoencoder
Implementations of the models in the paper “Deconvolutional Paragraph Representation Learning” by Yizhe Zhang, Dinghan Shen, Guoyin Wang, Zhe Gan, Ricardo Henao and Lawrence Carin, NIPS 2017

pix2pixHD
Synthesizing and manipulating 2048×1024 images with conditional GANs

PyTorch Unsupervised Sentiment Discovery
Unsupervised Language Modeling at scale for robust sentiment classification

Libraries

probtorch
Probabilistic Torch is library for deep generative models that extends PyTorch

receptivefield
Gradient based receptive field estimation for Convolutional Neural Networks

XLearning
AI on Hadoop

TOROS N2
A lightweight approximate Nearest Neighbor library which runs faster even with large datasets

Nvidia Cutlass
CUDA Templates for Linear Algebra Subroutines

 


Looking into adding your repo? tweet to @stkim1!

 

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