harvardnlp

An annotated implementation of the Transformer paper.

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

Neural model for converting Image-to-Markup (by Yuntian Deng yuntiandeng.com)

Fast, general, and tested differentiable structured prediction in PyTorch

Text classification using a convolutional neural network.

Named Tensor implementation for Torch

Latent Alignment and Variational Attention

Code for Structured Attention Networks https://arxiv.org/abs/1702.00887

STEGASURAS: STEGanography via Arithmetic coding and Strong neURAl modelS

Topological botnet detection datasets and graph neural network applications

Cascaded Text Generation with Markov Transformers

Decomposable Attention Model for Sentence Pair Classification (from https://arxiv.org/abs/1606.01933)

CUDA kernels for generalized matrix-multiplication in PyTorch

Encoder-Agnostic Adaptation for Conditional Language Generation

Neural Machine Translation on Android