<p>RNN models trained on MS-COCO used in the following paper:</p> <p>Ákos Kádár, Grzegorz Chrupała, Afra Alishahi. 2017. "Representation of<br> linguistic form and function in recurrent neural networks". <em>Computational Linguistics.</em><br> </p
The thesis focuses on exploring extensions to the recurrent neural network (RNN) algorithm for natur...
Recurrent neural networks (RNNs) offer flexible machine learning tools which share the learning abil...
This repository contains the raw results (by word information-theoretic measures for the experimenta...
We present novel methods for analyzing the activation patterns of recurrent neural networks from a l...
ABSTRACT We present several modifications of the original recurrent neural network language model (R...
In this paper we present a survey on the application of recurrent neural networks to the task of sta...
Comunicació presentada a la 2016 Conference of the North American Chapter of the Association for Com...
© 2015 Association for Computational Linguistics. We investigate an extension of continuous online l...
The very promising reported results of Neural Networks grammar modelling has motivated a lot of rese...
Recurrent neural network (RNN) language models that are trained on large text corpora have shown a r...
AbstractIn this paper, we present a survey on the application of recurrent neural networks to the ta...
Recurrent neural networks (RNNs) are exceptionally good models of distributions over natural languag...
The present work takes into account the compactness and efficiency of Recurrent Neural Networks (RNN...
We describe a simple neural language model that re-lies only on character-level inputs. Predictions ...
We describe a simple neural language model that relies only on character-level inputs. Predictions a...
The thesis focuses on exploring extensions to the recurrent neural network (RNN) algorithm for natur...
Recurrent neural networks (RNNs) offer flexible machine learning tools which share the learning abil...
This repository contains the raw results (by word information-theoretic measures for the experimenta...
We present novel methods for analyzing the activation patterns of recurrent neural networks from a l...
ABSTRACT We present several modifications of the original recurrent neural network language model (R...
In this paper we present a survey on the application of recurrent neural networks to the task of sta...
Comunicació presentada a la 2016 Conference of the North American Chapter of the Association for Com...
© 2015 Association for Computational Linguistics. We investigate an extension of continuous online l...
The very promising reported results of Neural Networks grammar modelling has motivated a lot of rese...
Recurrent neural network (RNN) language models that are trained on large text corpora have shown a r...
AbstractIn this paper, we present a survey on the application of recurrent neural networks to the ta...
Recurrent neural networks (RNNs) are exceptionally good models of distributions over natural languag...
The present work takes into account the compactness and efficiency of Recurrent Neural Networks (RNN...
We describe a simple neural language model that re-lies only on character-level inputs. Predictions ...
We describe a simple neural language model that relies only on character-level inputs. Predictions a...
The thesis focuses on exploring extensions to the recurrent neural network (RNN) algorithm for natur...
Recurrent neural networks (RNNs) offer flexible machine learning tools which share the learning abil...
This repository contains the raw results (by word information-theoretic measures for the experimenta...
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