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Recursive neural network

A recursive neural network (RNN) is a kind of deep neural network created by applying the same set of weights recursively over a structure, to… 
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Artificial intelligence
Artificial neural networkBackpropagation through structureBackpropagation through timeDeep learning

Papers overview

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2018
2018
Learning sentence embeddings using Recursive Networks
Learning sentence vectors that generalise well is a challenging task. In this paper we compare three methods of learning phrase… 
2018
2018
A Deep Recursive Neural Network Model for Fine-Grained Opinion Classification
In recent times, deep neural networks (DNN) have acquired greater significance in providing solutions to many deep learning tasks… 
2017
2017
Collective Vertex Classification Using Recursive Neural Network
Collective classification of vertices is a task of assigning categories to each vertex in a graph based on both vertex attributes… 
2015
2015
Making a Manageable Email Experience with Deep Learning Final Report
This paper uses Deep Learning algorithms in the context of Natural Language Processing (NLP) and more specifically applies them… 
2015
2015
Recursive Nested Neural Network for Sentiment Analysis
Early sentiment prediction systems use semantic vector representation of words to express longer phrases and sentences. These… 
2014
2014
Self-learning recursive neural networks for structured data classification
Automatic classification of structured data is a challenging task and its relevance to many domains is evident. However… 
2004
2004
Predicting Thermodynamic Properties from Molecular Structures by Recursive Neural Networks
The recursive neural networks deal with prediction tasks for compounds represented in a structured domain. These approaches allow… 
2004
2004
A preliminary experimental comparison of recursive neural networks and a tree kernel method for QSAR/QSPR regression tasks
We consider two different methods for QSAR/QSPR regres- sion tasks: Recursive Neural Networks (RecNN) and a Support Vector… 
2003
2003
Comparing Convolution Kernels and Recursive Neural Networks for Learning Preferences on Structured Data
Convolution kernels and recursive neural networks (RNN) are both suitable approaches for supervised learning when the input… 
1993
1993
Recursive neural networks with high capacity
square root 3/sup n-1/ is derived as the lower bound of maximum capacity in n-neuron recursive neural networks. It is shown that…