Must-read papers on Machine Reading Comprehension

A PyTorch implementation of Google AI's BERT model provided with Google's pre-trained models, examples and utilities.

python版本：高准确度中文分词工具，简单易用，跟现有开源工具相比大幅提高了分词的准确率。

Fast Neural Machine Translation in C++

Stochastic Answer Networks (SAN) for Machine Reading Comprehension

A curated list of papers dedicated to neural text (semantic) matching.

Google AI 2018 BERT pytorch implementation

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

Hierarchical BiLSTM max pooling architecture for NLI

A pedagogical implementation of Autograd

Re-implementation of BIMPM(Bilateral Multi-Perspective Matching for Natural Language Sentences, Zhiguo Wang et al.) on Pytorch.

Tensors and Dynamic neural networks in Python with strong GPU acceleration

A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Torch and Numpy.

Implementation and evaluation of different approaches to get uncertainty in neural networks

This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.