Aaron van den Oord

research

∙ 08/07/2023

AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning

StarCraft II is one of the most challenging simulated reinforcement lear...

0 Michael Mathieu, et al. ∙

research

∙ 12/13/2021

Step-unrolled Denoising Autoencoders for Text Generation

In this paper we propose a new generative model of text, Step-unrolled D...

0 Nikolay Savinov, et al. ∙

research

∙ 11/23/2021

Towards Learning Universal Audio Representations

The ability to learn universal audio representations that can solve dive...

0 Luyu Wang, et al. ∙

research

∙ 06/08/2021

Vector Quantized Models for Planning

Recent developments in the field of model-based RL have proven successfu...

0 Sherjil Ozair, et al. ∙

research

∙ 05/17/2021

Divide and Contrast: Self-supervised Learning from Uncurated Data

Self-supervised learning holds promise in leveraging large amounts of un...

0 Yonglong Tian, et al. ∙

research

∙ 04/26/2021

Multimodal Self-Supervised Learning of General Audio Representations

We present a multimodal framework to learn general audio representations...

0 Luyu Wang, et al. ∙

research

∙ 03/30/2021

Broaden Your Views for Self-Supervised Video Learning

Most successful self-supervised learning methods are trained to align th...

3 Adria Recasens, et al. ∙

research

∙ 03/19/2021

Efficient Visual Pretraining with Contrastive Detection

Self-supervised pretraining has been shown to yield powerful representat...

0 Olivier J. Hénaff, et al. ∙

research

∙ 03/11/2021

Multi-Format Contrastive Learning of Audio Representations

Recent advances suggest the advantage of multi-modal training in compari...

0 Luyu Wang, et al. ∙

research

∙ 03/02/2021

Predicting Video with VQVAE

In recent years, the task of video prediction-forecasting future video g...

0 Jacob Walker, et al. ∙

research

∙ 06/12/2020

Are we done with ImageNet?

Yes, and no. We ask whether recent progress on the ImageNet classificati...

11 Lucas Beyer, et al. ∙

research

∙ 01/29/2020

Learning Robust and Multilingual Speech Representations

Unsupervised speech representation learning has shown remarkable success...

0 Kazuya Kawakami, et al. ∙

research

∙ 10/14/2019

Low Bit-Rate Speech Coding with VQ-VAE and a WaveNet Decoder

In order to efficiently transmit and store speech signals, speech codecs...

11 Cristina Garbacea, et al. ∙

research

∙ 06/21/2019

Shaping Belief States with Generative Environment Models for RL

When agents interact with a complex environment, they must form and main...

3 Karol Gregor, et al. ∙

research

∙ 06/02/2019

Generating Diverse High-Fidelity Images with VQ-VAE-2

We explore the use of Vector Quantized Variational AutoEncoder (VQ-VAE) ...

4 Ali Razavi, et al. ∙

research

∙ 05/22/2019

Data-Efficient Image Recognition with Contrastive Predictive Coding

Large scale deep learning excels when labeled images are abundant, yet d...

3 Olivier J. Hénaff, et al. ∙

research

∙ 05/16/2019

On Variational Bounds of Mutual Information

Estimating and optimizing Mutual Information (MI) is core to many proble...

8 Ben Poole, et al. ∙

research

∙ 03/28/2019

Wasserstein Dependency Measure for Representation Learning

Mutual information maximization has emerged as a powerful learning objec...

18 Sherjil Ozair, et al. ∙

research

∙ 01/25/2019

Unsupervised speech representation learning using WaveNet autoencoders

We consider the task of unsupervised extraction of meaningful latent rep...

12 Jan Chorowski, et al. ∙

research

∙ 01/10/2019

Preventing Posterior Collapse with delta-VAEs

Due to the phenomenon of "posterior collapse," current latent variable g...

4 Ali Razavi, et al. ∙

research

∙ 09/27/2018

Sample Efficient Adaptive Text-to-Speech

We present a meta-learning approach for adaptive text-to-speech (TTS) wi...

2 Yutian Chen, et al. ∙

research

∙ 07/10/2018

Representation Learning with Contrastive Predictive Coding

While supervised learning has enabled great progress in many application...

0 Aaron van den Oord, et al. ∙

research

∙ 06/26/2018

The challenge of realistic music generation: modelling raw audio at scale

Realistic music generation is a challenging task. When building generati...

6 Sander Dieleman, et al. ∙

research

∙ 04/06/2018

Associative Compression Networks for Representation Learning

This paper introduces Associative Compression Networks (ACNs), a new fra...

0 Alex Graves, et al. ∙

research

∙ 04/06/2018

Associative Compression Networks

This paper introduces Associative Compression Networks (ACNs), a new fra...

0 Alex Graves, et al. ∙

research

∙ 02/23/2018

Efficient Neural Audio Synthesis

Sequential models achieve state-of-the-art results in audio, visual and ...

0 Nal Kalchbrenner, et al. ∙

research

∙ 02/15/2018

Adversarial Risk and the Dangers of Evaluating Against Weak Attacks

This paper investigates recently proposed approaches for defending again...

0 Jonathan Uesato, et al. ∙

research

∙ 11/28/2017

Parallel WaveNet: Fast High-Fidelity Speech Synthesis

The recently-developed WaveNet architecture is the current state of the ...

0 Aaron van den Oord, et al. ∙

research

∙ 10/27/2017

Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions

Deep autoregressive models have shown state-of-the-art performance in de...

0 Scott Reed, et al. ∙

research

∙ 03/10/2017

Parallel Multiscale Autoregressive Density Estimation

PixelCNN achieves state-of-the-art results in density estimation for nat...

0 Scott Reed, et al. ∙

research

∙ 10/31/2016

Neural Machine Translation in Linear Time

We present a novel neural network for processing sequences. The ByteNet ...

0 Nal Kalchbrenner, et al. ∙

research

∙ 10/03/2016

Video Pixel Networks

We propose a probabilistic video model, the Video Pixel Network (VPN), t...

0 Nal Kalchbrenner, et al. ∙

research

∙ 09/12/2016

WaveNet: A Generative Model for Raw Audio

This paper introduces WaveNet, a deep neural network for generating raw ...

0 Aaron van den Oord, et al. ∙

research

∙ 06/16/2016

Conditional Image Generation with PixelCNN Decoders

This work explores conditional image generation with a new image density...

0 Aaron van den Oord, et al. ∙

research

∙ 01/25/2016

Pixel Recurrent Neural Networks

Modeling the distribution of natural images is a landmark problem in uns...

0 Aaron van den Oord, et al. ∙

research

∙ 11/05/2015

A note on the evaluation of generative models

Probabilistic generative models can be used for compression, denoising, ...

0 Lucas Theis, et al. ∙

research

∙ 06/05/2015

Beyond Temporal Pooling: Recurrence and Temporal Convolutions for Gesture Recognition in Video

Recent studies have demonstrated the power of recurrent neural networks ...

0 Lionel Pigou, et al. ∙

Aaron van den Oord

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