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04/29/2022
Flamingo: a Visual Language Model for Few-Shot Learning
Building models that can be rapidly adapted to numerous tasks using only...
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03/29/2022
Training Compute-Optimal Large Language Models
We investigate the optimal model size and number of tokens for training ...
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02/22/2022
Hierarchical Perceiver
General perception systems such as Perceivers can process arbitrary moda...
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02/02/2022
Unified Scaling Laws for Routed Language Models
The performance of a language model has been shown to be effectively mod...
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12/08/2021
Improving language models by retrieving from trillions of tokens
We enhance auto-regressive language models by conditioning on document c...
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04/12/2021
Machine Translation Decoding beyond Beam Search
Beam search is the go-to method for decoding auto-regressive machine tra...
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04/02/2021
Skillful Precipitation Nowcasting using Deep Generative Models of Radar
Precipitation nowcasting, the high-resolution forecasting of precipitati...
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03/10/2021
Variable-rate discrete representation learning
Semantically meaningful information content in perceptual signals is usu...
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02/11/2021
High-Performance Large-Scale Image Recognition Without Normalization
Batch normalization is a key component of most image classification mode...
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06/12/2020
AlgebraNets
Neural networks have historically been built layerwise from the set of f...
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06/12/2020
A Practical Sparse Approximation for Real Time Recurrent Learning
Current methods for training recurrent neural networks are based on back...
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06/05/2020
End-to-End Adversarial Text-to-Speech
Modern text-to-speech synthesis pipelines typically involve multiple pro...
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04/06/2020
Evolving Normalization-Activation Layers
Normalization layers and activation functions are critical components in...
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03/09/2020
Transformation-based Adversarial Video Prediction on Large-Scale Data
Recent breakthroughs in adversarial generative modeling have led to mode...
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12/02/2019
LOGAN: Latent Optimisation for Generative Adversarial Networks
Training generative adversarial networks requires balancing of delicate ...
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11/21/2019
Fast Sparse ConvNets
Historically, the pursuit of efficient inference has been one of the dri...
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11/19/2019
Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
Constructing agents with planning capabilities has long been one of the ...
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09/25/2019
High Fidelity Speech Synthesis with Adversarial Networks
Generative adversarial networks have seen rapid development in recent ye...
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09/25/2019
Off-Policy Actor-Critic with Shared Experience Replay
We investigate the combination of actor-critic reinforcement learning al...
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07/15/2019
Efficient Video Generation on Complex Datasets
Generative models of natural images have progressed towards high fidelit...
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07/04/2019
Large Scale Adversarial Representation Learning
Adversarially trained generative models (GANs) have recently achieved co...
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06/07/2019
Non-Differentiable Supervised Learning with Evolution Strategies and Hybrid Methods
In this work we show that Evolution Strategies (ES) are a viable method ...
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03/06/2019
Hierarchical Autoregressive Image Models with Auxiliary Decoders
Autoregressive generative models of images tend to be biased towards cap...
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03/04/2019
The StreetLearn Environment and Dataset
Navigation is a rich and well-grounded problem domain that drives progre...
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09/28/2018
Large Scale GAN Training for High Fidelity Natural Image Synthesis
Despite recent progress in generative image modeling, successfully gener...
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08/10/2018
This Time with Feeling: Learning Expressive Musical Performance
Music generation has generally been focused on either creating scores or...
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06/26/2018
The challenge of realistic music generation: modelling raw audio at scale
Realistic music generation is a challenging task. When building generati...
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06/24/2018
DARTS: Differentiable Architecture Search
This paper addresses the scalability challenge of architecture search by...
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03/31/2018
Learning to Navigate in Cities Without a Map
Navigating through unstructured environments is a basic capability of in...
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03/10/2018
Kickstarting Deep Reinforcement Learning
We present a method for using previously-trained 'teacher' agents to kic...
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02/23/2018
Efficient Neural Audio Synthesis
Sequential models achieve state-of-the-art results in audio, visual and ...
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02/13/2018
Learning to Search with MCTSnets
Planning problems are among the most important and well-studied problems...
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02/05/2018
IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
In this work we aim to solve a large collection of tasks using a single ...
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12/05/2017
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
The game of chess is the most widely-studied domain in the history of ar...
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11/28/2017
Parallel WaveNet: Fast High-Fidelity Speech Synthesis
The recently-developed WaveNet architecture is the current state of the ...
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11/27/2017
Population Based Training of Neural Networks
Neural networks dominate the modern machine learning landscape, but thei...
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11/01/2017
Hierarchical Representations for Efficient Architecture Search
We explore efficient neural architecture search methods and present a si...
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08/16/2017
StarCraft II: A New Challenge for Reinforcement Learning
This paper introduces SC2LE (StarCraft II Learning Environment), a reinf...
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05/19/2017
The Kinetics Human Action Video Dataset
We describe the DeepMind Kinetics human action video dataset. The datase...
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04/05/2017
Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders
Generative models in vision have seen rapid progress due to algorithmic ...
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10/31/2016
Neural Machine Translation in Linear Time
We present a novel neural network for processing sequences. The ByteNet ...
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10/03/2016
Video Pixel Networks
We propose a probabilistic video model, the Video Pixel Network (VPN), t...
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09/12/2016
WaveNet: A Generative Model for Raw Audio
This paper introduces WaveNet, a deep neural network for generating raw ...
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07/01/2015
Natural Neural Networks
We introduce Natural Neural Networks, a novel family of algorithms that ...
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06/05/2015
Spatial Transformer Networks
Convolutional Neural Networks define an exceptionally powerful class of ...
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12/18/2014
Deep Structured Output Learning for Unconstrained Text Recognition
We develop a representation suitable for the unconstrained recognition o...
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12/04/2014
Reading Text in the Wild with Convolutional Neural Networks
In this work we present an end-to-end system for text spotting -- locali...
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09/04/2014
Very Deep Convolutional Networks for Large-Scale Image Recognition
In this work we investigate the effect of the convolutional network dept...
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07/17/2014
Efficient On-the-fly Category Retrieval using ConvNets and GPUs
We investigate the gains in precision and speed, that can be obtained by...
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06/09/2014