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automl

Google Brain AutoML

bottom-up-attention-vqa

An efficient PyTorch implementation of the winning entry of the 2017 VQA Challenge.

cnn-text-classification-tf

Convolutional Neural Network for Text Classification in Tensorflow

dmn-tensorflow

Dynamic Memory Networks (https://arxiv.org/abs/1603.01417) in Tensorflow

dppnet

DPPnet: Image Question Answering using Convolutional Neural Network with Dynamic Parameter Prediction

fb.resnet.torch

Torch implementation of ResNet from http://arxiv.org/abs/1512.03385 and training scripts

hello-world

first rep

hiecoattenvqa

imagenet-validation.torch

Fast and easy testing of imagenet models

imageqa-public

Code for paper "Exploring Models and Data for Image Question Answering"

imageqa-san

code for Stacked attention networks for image question answering

joint-bayesian

Face verify using Joint Bayesian, implemented by Python

lantern

:zap: Open Internet for everyone. Lantern is a free desktop application that delivers fast, reliable and secure access to the open Internet for users in censored regions. It uses a variety of techniques to stay unblocked, including P2P and domain fronting. Lantern relies on users in uncensored regions acting as access points to the open Internet.

pygrid

Automatically exported from code.google.com/p/pygrid

rau_vqa

Training Recurrent Answering Units with Joint Loss Minimization for VQA

readme

README文件语法解读，即Github Flavored Markdown语法介绍

skip-thoughts

Sent2Vec encoder and training code from the paper "Skip-Thought Vectors"

torch-lsuv

Torch implementation of LSUV weight init from http://arxiv.org/abs/1511.06422

visual7w-qa-models

Visual7W visual question answering models

vqa.pytorch

Visual Question Answering in Pytorch

vqabaseline

Simple Baseline for Visual Question Answering