Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks

IJCNLP 2015 8 code implementations

Because of their superior ability to preserve sequence information over time, Long Short-Term Memory (LSTM) networks, a type of recurrent neural network with a more complex computational unit, have obtained strong results on a variety of sequence modeling tasks.

SENTIMENT ANALYSIS

Bidirectional Quaternion Long-Short Term Memory Recurrent Neural Networks for Speech Recognition

6 Nov 20181 code implementation

Recurrent neural networks (RNN) are at the core of modern automatic speech recognition (ASR) systems.

SPEECH RECOGNITION

Predicting Domain Generation Algorithms with Long Short-Term Memory Networks

2 Nov 20161 code implementation

Another technique to stop malware from using DGAs is to intercept DNS queries on a network and predict whether domains are DGA generated.

Top-down Tree Long Short-Term Memory Networks

NAACL 2016 1 code implementation

Long Short-Term Memory (LSTM) networks, a type of recurrent neural network with a more complex computational unit, have been successfully applied to a variety of sequence modeling tasks.

DEPENDENCY PARSING

Dual Long Short-Term Memory Networks for Sub-Character Representation Learning

23 Dec 20171 code implementation

To build a concrete study and substantiate the efficiency of our neural architecture, we take Chinese Word Segmentation as a research case example.

CHINESE WORD SEGMENTATION REPRESENTATION LEARNING

Part-of-Speech Tagging with Bidirectional Long Short-Term Memory Recurrent Neural Network

21 Oct 20153 code implementations

Bidirectional Long Short-Term Memory Recurrent Neural Network (BLSTM-RNN) has been shown to be very effective for tagging sequential data, e. g. speech utterances or handwritten documents.

PART-OF-SPEECH TAGGING

Drug-Drug Interaction Extraction from Biomedical Text Using Long Short Term Memory Network

28 Jan 20171 code implementation

The two models, {\it AB-LSTM} and {\it Joint AB-LSTM} also use attentive pooling in the output of Bi-LSTM layer to assign weights to features.

FEATURE ENGINEERING MEDICAL RELATION EXTRACTION

PICO Element Detection in Medical Text via Long Short-Term Memory Neural Networks

WS 2018 2 code implementations

Successful evidence-based medicine (EBM) applications rely on answering clinical questions by analyzing large medical literature databases.

DECISION MAKING

Simplified Gating in Long Short-term Memory (LSTM) Recurrent Neural Networks

12 Jan 20171 code implementation

The standard LSTM recurrent neural networks while very powerful in long-range dependency sequence applications have highly complex structure and relatively large (adaptive) parameters.