3.6k citations · 10k across the 28 of their papers we have counts for
5 papers · 1 filter
Neural Machine Translation in Linear Time
Nal Kalchbrenner, Lasse Espeholt, Karen Simonyan +3
We present a novel neural network for processing sequences. The ByteNet is a one-dimensional convolutional neural network that is composed of two parts, one to encode the source se…
Resolving Lexical Ambiguity in Tensor Regression Models of Meaning
Dimitri Kartsaklis, Nal Kalchbrenner, Mehrnoosh Sadrzadeh
This paper provides a method for improving tensor-based compositional distributional models of meaning by the addition of an explicit disambiguation step prior to composition. In c…
Modelling, Visualising and Summarising Documents with a Single Convolutional Neural Network
Misha Denil, Alban Demiraj, Nal Kalchbrenner +2
Capturing the compositional process which maps the meaning of words to that of documents is a central challenge for researchers in Natural Language Processing and Information Retri…
A Convolutional Neural Network for Modelling Sentences
Nal Kalchbrenner, Edward Grefenstette, Phil Blunsom
The ability to accurately represent sentences is central to language understanding. We describe a convolutional architecture dubbed the Dynamic Convolutional Neural Network (DCNN)…
Recurrent Convolutional Neural Networks for Discourse Compositionality
Nal Kalchbrenner, Phil Blunsom
The compositionality of meaning extends beyond the single sentence. Just as words combine to form the meaning of sentences, so do sentences combine to form the meaning of paragraph…