Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch

Efficient, reusable RNNs and LSTMs for torch

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

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

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

Recurrent Neural Network library for Torch7's nn

Tree-structured Long Short-Term Memory networks (http://arxiv.org/abs/1503.00075)

Neural conversational model in Torch

Light your way in Deep Learning with Torch 🔦

Raster-to-Vector: Revisiting Floorplan Transformation

Learning to Execute

Torch-7 FFI bindings for NVIDIA CuDNN

Implements an efficient softmax approximation as described in the paper "Efficient softmax approximation for GPUs" (http://arxiv.org/abs/1609.04309)

A deep learning library for streamlining research and development using the Torch7 distribution.

Practical 6: LSTM language models

OpenCV bindings for Torch.

A numeric optimization package for Torch.

deep extensions to nn

This library provides utilities for creating and manipulating RNNs to model sequential data.

中文短文句相似读

OpenCL backend for Torch nn neural networks library

Multi-Perspective Convolutional Neural Networks for modeling textual similarity (He et al., EMNLP 2015)

Some advanced tricks with Torch7 explained easily

Torch implementation of seq2seq machine translation with GRU RNN and attention

Armor for Openwrt

Torch recurrent neural networks

Recurrent modules for Torch

Modelling Sentence Pairs with Tree-structured Attentive Encoder https://arxiv.org/pdf/1610.02806.pdf

utility code for doing deep nlp in torch