Nal Kalchbrenner

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WaveNet: A Generative Model for Raw Audio

Aäron van den Oord, Sander Dieleman, +6 authors Koray Kavukcuoglu
SSW
2016

This paper introduces WaveNet, a deep neural network for generating raw audio waveforms. The model is fully probabilistic and autoregressive, with the predictive distribution for each audio sample… (More)

Mastering the game of Go with deep neural networks and tree search

David Silver, Aja Huang, +17 authors Demis Hassabis
Nature
2016

The game of Go has long been viewed as the most challenging of classic games for artificial intelligence owing to its enormous search space and the difficulty of evaluating board positions and moves.… (More)

A Convolutional Neural Network for Modelling Sentences

Nal Kalchbrenner, Edward Grefenstette, Phil Blunsom
ACL
2014

The ability to accurately represent sentences is central to language understanding. We describe a convolutional architecture dubbed the Dynamic Convolutional Neural Network (DCNN) that we adopt for… (More)

Pixel Recurrent Neural Networks

Aäron van den Oord, Nal Kalchbrenner, Koray Kavukcuoglu
ICML
2016

Modeling the distribution of natural images is a landmark problem in unsupervised learning. This task requires an image model that is at once expressive, tractable and scalable. We present a deep… (More)

Conditional Image Generation with PixelCNN Decoders

Aäron van den Oord, Nal Kalchbrenner, Oriol Vinyals, Lasse Espeholt, Alex Graves, Koray Kavukcuoglu
NIPS
2016

This work explores conditional image generation with a new image density model based on the PixelCNN architecture. The model can be conditioned on any vector, including descriptive labels or tags, or… (More)

Grid Long Short-Term Memory

Nal Kalchbrenner, Ivo Danihelka, Alex Graves
ICLR
2015

This paper introduces Grid Long Short-Term Memory, a network of LSTM cells arranged in a multidimensional grid that can be applied to vectors, sequences or higher dimensional data such as images. The… (More)

Recurrent Continuous Translation Models

We introduce a class of probabilistic continuous translation models called Recurrent Continuous Translation Models that are purely based on continuous representations for words, phrases and sentences… (More)

Parallel WaveNet: Fast High-Fidelity Speech Synthesis

Aäron van den Oord, Yazhe Li, +19 authors Demis Hassabis
ICML
2017

The recently-developed WaveNet architecture is the current state of the art in realistic speech synthesis, consistently rated as more natural sounding for many different languages than any previous… (More)

Neural Machine Translation in Linear Time

Nal Kalchbrenner, Lasse Espeholt, Karen Simonyan, Aäron van den Oord, Alex Graves, Koray Kavukcuoglu
ArXiv
2016

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 sequence and the… (More)

Recurrent Convolutional Neural Networks for Discourse Compositionality

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 paragraphs, dialogues and… (More)

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