b'Oriol Vinyals'

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

∙ 06/12/2023

Waffling around for Performance: Visual Classification with Random Words and Broad Concepts

The visual classification performance of vision-language models such as ...

0 Karsten Roth, et al. ∙

research

∙ 05/11/2023

Optimizing Memory Mapping Using Deep Reinforcement Learning

Resource scheduling and allocation is a critical component of many high ...

0 Pengming Wang, et al. ∙

research

∙ 12/24/2022

GraphCast: Learning skillful medium-range global weather forecasting

We introduce a machine-learning (ML)-based weather simulator–called "Gra...

0 Remi Lam, et al. ∙

research

∙ 05/12/2022

A Generalist Agent

Inspired by progress in large-scale language modeling, we apply a simila...

12 Scott Reed, et al. ∙

research

∙ 04/29/2022

Flamingo: a Visual Language Model for Few-Shot Learning

Building models that can be rapidly adapted to numerous tasks using only...

7 Jean-Baptiste Alayrac, et al. ∙

research

∙ 03/29/2022

Training Compute-Optimal Large Language Models

We investigate the optimal model size and number of tokens for training ...

6 Jordan Hoffmann, et al. ∙

research

∙ 03/16/2022

Non-isotropy Regularization for Proxy-based Deep Metric Learning

Deep Metric Learning (DML) aims to learn representation spaces on which ...

17 Karsten Roth, et al. ∙

research

∙ 03/16/2022

Integrating Language Guidance into Vision-based Deep Metric Learning

Deep Metric Learning (DML) proposes to learn metric spaces which encode ...

9 Karsten Roth, et al. ∙

research

∙ 02/22/2022

Hierarchical Perceiver

General perception systems such as Perceivers can process arbitrary moda...

2 Joao Carreira, et al. ∙

research

∙ 02/15/2022

General-purpose, long-context autoregressive modeling with Perceiver AR

Real-world data is high-dimensional: a book, image, or musical performan...

2 Curtis Hawthorne, et al. ∙

research

∙ 02/14/2022

MuZero with Self-competition for Rate Control in VP9 Video Compression

Video streaming usage has seen a significant rise as entertainment, educ...

0 Amol Mandhane, et al. ∙

research

∙ 02/08/2022

Competition-Level Code Generation with AlphaCode

Programming is a powerful and ubiquitous problem-solving tool. Developin...

0 Yujia Li, et al. ∙

research

∙ 02/02/2022

Unified Scaling Laws for Routed Language Models

The performance of a language model has been shown to be effectively mod...

2 Aidan Clark, et al. ∙

research

∙ 12/08/2021

Improving language models by retrieving from trillions of tokens

We enhance auto-regressive language models by conditioning on document c...

8 Sebastian Borgeaud, et al. ∙

research

∙ 07/30/2021

Perceiver IO: A General Architecture for Structured Inputs Outputs

The recently-proposed Perceiver model obtains good results on several do...

6 Andrew Jaegle, et al. ∙

research

∙ 07/20/2021

WikiGraphs: A Wikipedia Text - Knowledge Graph Paired Dataset

We present a new dataset of Wikipedia articles each paired with a knowle...

65 Luyu Wang, et al. ∙

research

∙ 07/14/2021

The Benchmark Lottery

The world of empirical machine learning (ML) strongly relies on benchmar...

8 Mostafa Dehghani, et al. ∙

research

∙ 06/25/2021

Multimodal Few-Shot Learning with Frozen Language Models

When trained at sufficient scale, auto-regressive language models exhibi...

0 Maria Tsimpoukelli, 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

∙ 04/12/2021

Machine Translation Decoding beyond Beam Search

Beam search is the go-to method for decoding auto-regressive machine tra...

0 Rémi Leblond, 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

∙ 03/04/2021

Perceiver: General Perception with Iterative Attention

Biological systems understand the world by simultaneously processing hig...

18 Andrew Jaegle, et al. ∙

research

∙ 01/26/2021

The MineRL 2020 Competition on Sample Efficient Reinforcement Learning using Human Priors

Although deep reinforcement learning has led to breakthroughs in many di...

11 William H. Guss, et al. ∙

research

∙ 12/23/2020

Solving Mixed Integer Programs Using Neural Networks

Mixed Integer Programming (MIP) solvers rely on an array of sophisticate...

9 Vinod Nair, et al. ∙

research

∙ 07/17/2020

AlignNet: Unsupervised Entity Alignment

Recently developed deep learning models are able to learn to segment sce...

35 Antonia Creswell, et al. ∙

research

∙ 07/07/2020

Strong Generalization and Efficiency in Neural Programs

We study the problem of learning efficient algorithms that strongly gene...

11 Yujia Li, et al. ∙

research

∙ 06/11/2020

Pointer Graph Networks

Graph neural networks (GNNs) are typically applied to static graphs that...

33 Petar Veličković, et al. ∙

research

∙ 03/10/2020

The MineRL Competition on Sample-Efficient Reinforcement Learning Using Human Priors: A Retrospective

To facilitate research in the direction of sample-efficient reinforcemen...

9 Stephanie Milani, et al. ∙

research

∙ 03/10/2020

Retrospective Analysis of the 2019 MineRL Competition on Sample Efficient Reinforcement Learning

To facilitate research in the direction of sample-efficient reinforcemen...

0 Stephanie Milani, 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

∙ 10/02/2019

Unsupervised Doodling and Painting with Improved SPIRAL

We investigate using reinforcement learning agents as generative models ...

13 John F. J. Mellor, et al. ∙

research

∙ 09/19/2019

Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML

An important research direction in machine learning has centered around ...

5 Aniruddh Raghu, 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

∙ 05/26/2019

Classification Accuracy Score for Conditional Generative Models

Deep generative models (DGMs) of images are now sufficiently mature that...

4 Suman Ravuri, et al. ∙

research

∙ 05/07/2019

REGAL: Transfer Learning For Fast Optimization of Computation Graphs

We present a deep reinforcement learning approach to optimizing the exec...

14 Aditya Paliwal, et al. ∙

research

∙ 04/29/2019

Graph Matching Networks for Learning the Similarity of Graph Structured Objects

This paper addresses the challenging problem of retrieval and matching o...

8 Yujia Li, et al. ∙

research

∙ 01/17/2019

Attentive Neural Processes

Neural Processes (NPs) (Garnelo et al 2018a;b) approach regression by le...

10 Hyunjik Kim, 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

∙ 12/03/2018

Generating Diverse Programs with Instruction Conditioned Reinforced Adversarial Learning

Advances in Deep Reinforcement Learning have led to agents that perform ...

0 Aishwarya Agrawal, 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

∙ 09/06/2018

Deep Audio-Visual Speech Recognition

The goal of this work is to recognise phrases and sentences being spoken...

2 Triantafyllos Afouras, et al. ∙

research

∙ 07/16/2018

Meta-Learning with Latent Embedding Optimization

Gradient-based meta-learning techniques are both widely applicable and p...

0 Andrei A. Rusu, et al. ∙

research

∙ 07/10/2018

Universal Transformers

Self-attentive feed-forward sequence models have been shown to achieve i...

6 Mostafa Dehghani, 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

∙ 06/28/2018

Learning Implicit Generative Models with the Method of Learned Moments

We propose a method of moments (MoM) algorithm for training large-scale ...

2 Suman Ravuri, et al. ∙

research

∙ 06/05/2018

Relational Deep Reinforcement Learning

We introduce an approach for deep reinforcement learning (RL) that impro...

0 Vinicius Zambaldi, et al. ∙

research

∙ 06/05/2018

Relational recurrent neural networks

Memory-based neural networks model temporal data by leveraging an abilit...

2 Adam Santoro, et al. ∙

research

∙ 06/04/2018

Relational inductive biases, deep learning, and graph networks

Artificial intelligence (AI) has undergone a renaissance recently, makin...

0 Peter W. Battaglia, et al. ∙

research

∙ 04/18/2018

A Study on Overfitting in Deep Reinforcement Learning

Recent years have witnessed significant progresses in deep Reinforcement...

0 Chiyuan Zhang, et al. ∙

Oriol Vinyals

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