taineleau-zz

julia

The Julia Programming Language

jax

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

labelme

Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).

python-socketio

Python Socket.IO server and client

transformer-xl

awesome-deep-learning-music

List of articles related to deep learning applied to music

CSrankings

A web app for ranking computer science departments according to their research output in selective venues, and for finding active faculty across a wide range of areas.

vatic

Efficiently Scaling Up Video Annotation with Crowdsourced Marketplaces. IJCV 2012

Luxor.jl

Simple drawings using vector graphics; Cairo "for tourists!"

CUDAnative.jl

Julia support for native CUDA programming

spreadingvectors

Open source implementation of "Spreading Vectors for Similarity Search"

mak-mini

A (small) piece of paper.

neural-template-gen

constrained-graph-variational-autoencoder

Sample code for Constrained Graph Variational Autoencoders

draco

Visualization Constraints and Weight Learning

FlowQA

Implementation of conversational QA model: FlowQA (with slight improvement)

vae-lagging-encoder

PyTorch implementation of "Lagging Inference Networks and Posterior Collapse in Variational Autoencoders" (ICLR 2019)

qcircuit

A quantum circuit drawing application

macarico

learning to search in pytorch

turkserver-meteor

Web-based, real-time behavioral studies and experiments using Meteor

dogTorch

Who Let The Dogs Out? Modeling Dog Behavior From Visual Data https://arxiv.org/pdf/1803.10827.pdf

wxpay-sdk

Server-side SDK of Weixin/WeChat, the Java binding.

amti

A Mechanical Turk Interface (amti) 🤖

AMR_AS_GRAPH_PREDICTION

viznet

network visualization toolkit

SPIGOT

pytorch-conv4d

Conv4d in PyTroch

Turker

Python framework for Amazon Mechanical Turk

Compensate-MTurk-HIT

As a requester, if something went wrong with your HIT on Amazon Mechanical Turk, turkers would ask you to compensate their wasted time and effort. You can simply use this code to create an external "Compensate HIT".