Introduction

• The paper introduces a novel architecture that generates an output sequence...
  

Introduction

• Word based language models suffer from the problem of rare or...
  

Introduction

• R-NET is an end-to-end trained neural network model for machine comprehension.

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Introduction

• In the domain of machine comprehension, making multiple passes over the...
  

Problem Statement

• Given a pre-trained neural network, which is trained using data...
  

Introduction

• Dynamic Memory Networks (DMN) is a neural network based general framework...
  

• The current trend in deep learning is to design, train and fine tune...
  

• The paper proposes two variants of Word2Vec model so that it may account for...
  

Introduction

• The paper proposes an attention based mechanism to decompose the problem of...
  

Introduction

• The paper proposes a neural network classifier to perform transition-based dependency parsing...