There are 0 repository under dynet topic.
A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks
A collection of datasets that pair questions with SQL queries.
Simple Solution for Multi-Criteria Chinese Word Segmentation
A frame-semantic parsing system based on a softmax-margin SegRNN.
BiLSTM-CRF for sequence labeling in Dynet
Code for paper "End-to-End Reinforcement Learning for Automatic Taxonomy Induction", ACL 2018
An Implementation of Transformer (Attention Is All You Need) in DyNet
Transition-based joint syntactic dependency parser and semantic role labeler using a stack LSTM RNN architecture.
Deep Recurrent Generative Decoder for Abstractive Text Summarization in DyNet
Dataset and model for disentangling chat on IRC
Code for the paper "Extreme Adaptation for Personalized Neural Machine Translation"
Source code for the paper "Morphological Inflection Generation with Hard Monotonic Attention"
An attentional NMT model in Dynet
See http://github.com/onurgu/joint-ner-and-md-tagger This repository is basically a Bi-LSTM based sequence tagger in both Tensorflow and Dynet which can utilize several sources of information about each word unit like word embeddings, character based embeddings and morphological tags from an FST to obtain the representation for that specific word unit.
DyNet implementation of stack LSTM experiments by Grefenstette et al.
Selective Encoding for Abstractive Sentence Summarization in DyNet
A Neural Attention Model for Abstractive Sentence Summarization in DyNet
Neural morphological disambiguation for Turkish. Implemented in DyNet
Turkish Morphological Analyzer with dictionaries for stems and suffixes + Neural Morphological Disambiguation implemented in DyNet
Convolutional Neural Networks for Sentence Classification in DyNet
Greedy, Joint Syntactic-Semantic Parsing with Stack LSTMs
miRNA subcellular localization
PoS Tagging with Bidirectional Long Short-Term Memory Models
Code that exemplifies neural network solutions for classification tasks with DyNet. On top of that, the code demonstrates how to implement a custom classifier that is compatible with scikit-learn's API.
a simple modification of Chris Dyer's stack LSTM Parser
Neural Machine Translation with Attention (Dynet)
Port of DYNET to JavaScript with p5.js visualization