PyTorch implementation of recurrent neural network encoder-decoder architecture model for statistical machine translation, as detailed in this paper: Learning Phrase Representations using RNN ...

This project implements an Automatic Image Captioning model based on encoder-decoder CNN-RNN architecture trained on COCO dataset. Model is able to generate statements about input image. ... To ...

An Encoder-decoder architecture in machine learning efficiently translates one sequence data form to another. ... especially for traditional recurrent neural network (RNN)-based encoders.

This article explores some of the most influential deep learning architectures: Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), ...

We propose a single-document abstractive summarization system that integrates token relation into a traditional RNN-based encoder-decoder architecture. We employ pointer-wise mutual information to ...

Since the deep learning boom has started, numerous researchers have started building many architectures around neural networks. It is often speculated that the neural networks are inspired by neurons ...

We propose a single-document abstractive summarization system that integrates token relation into a traditional RNN-based encoder-decoder architecture. We employ pointer-wise mutual information to ...