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08/07/2023
AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning
StarCraft II is one of the most challenging simulated reinforcement lear...
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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 ...
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05/11/2023
Optimizing Memory Mapping Using Deep Reinforcement Learning
Resource scheduling and allocation is a critical component of many high ...
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12/24/2022
GraphCast: Learning skillful medium-range global weather forecasting
We introduce a machine-learning (ML)-based weather simulator–called "Gra...
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05/12/2022
A Generalist Agent
Inspired by progress in large-scale language modeling, we apply a simila...
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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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03/16/2022
Non-isotropy Regularization for Proxy-based Deep Metric Learning
Deep Metric Learning (DML) aims to learn representation spaces on which ...
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03/16/2022
Integrating Language Guidance into Vision-based Deep Metric Learning
Deep Metric Learning (DML) proposes to learn metric spaces which encode ...
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02/22/2022
Hierarchical Perceiver
General perception systems such as Perceivers can process arbitrary moda...
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02/15/2022
General-purpose, long-context autoregressive modeling with Perceiver AR
Real-world data is high-dimensional: a book, image, or musical performan...
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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...
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02/08/2022
Competition-Level Code Generation with AlphaCode
Programming is a powerful and ubiquitous problem-solving tool. Developin...
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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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07/30/2021
Perceiver IO: A General Architecture for Structured Inputs Outputs
The recently-proposed Perceiver model obtains good results on several do...
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07/20/2021
WikiGraphs: A Wikipedia Text - Knowledge Graph Paired Dataset
We present a new dataset of Wikipedia articles each paired with a knowle...
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07/14/2021
The Benchmark Lottery
The world of empirical machine learning (ML) strongly relies on benchmar...
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06/25/2021
Multimodal Few-Shot Learning with Frozen Language Models
When trained at sufficient scale, auto-regressive language models exhibi...
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06/08/2021
Vector Quantized Models for Planning
Recent developments in the field of model-based RL have proven successfu...
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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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03/19/2021
Efficient Visual Pretraining with Contrastive Detection
Self-supervised pretraining has been shown to yield powerful representat...
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03/04/2021
Perceiver: General Perception with Iterative Attention
Biological systems understand the world by simultaneously processing hig...
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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...
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12/23/2020
Solving Mixed Integer Programs Using Neural Networks
Mixed Integer Programming (MIP) solvers rely on an array of sophisticate...
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07/17/2020
AlignNet: Unsupervised Entity Alignment
Recently developed deep learning models are able to learn to segment sce...
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07/07/2020
Strong Generalization and Efficiency in Neural Programs
We study the problem of learning efficient algorithms that strongly gene...
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06/11/2020
Pointer Graph Networks
Graph neural networks (GNNs) are typically applied to static graphs that...
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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...
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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...
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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...
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10/02/2019
Unsupervised Doodling and Painting with Improved SPIRAL
We investigate using reinforcement learning agents as generative models ...
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09/19/2019
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML
An important research direction in machine learning has centered around ...
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06/02/2019
Generating Diverse High-Fidelity Images with VQ-VAE-2
We explore the use of Vector Quantized Variational AutoEncoder (VQ-VAE) ...
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05/26/2019
Classification Accuracy Score for Conditional Generative Models
Deep generative models (DGMs) of images are now sufficiently mature that...
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05/07/2019
REGAL: Transfer Learning For Fast Optimization of Computation Graphs
We present a deep reinforcement learning approach to optimizing the exec...
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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...
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01/17/2019
Attentive Neural Processes
Neural Processes (NPs) (Garnelo et al 2018a;b) approach regression by le...
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01/10/2019
Preventing Posterior Collapse with delta-VAEs
Due to the phenomenon of "posterior collapse," current latent variable g...
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12/03/2018
Generating Diverse Programs with Instruction Conditioned Reinforced Adversarial Learning
Advances in Deep Reinforcement Learning have led to agents that perform ...
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09/27/2018
Sample Efficient Adaptive Text-to-Speech
We present a meta-learning approach for adaptive text-to-speech (TTS) wi...
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09/06/2018
Deep Audio-Visual Speech Recognition
The goal of this work is to recognise phrases and sentences being spoken...
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07/16/2018
Meta-Learning with Latent Embedding Optimization
Gradient-based meta-learning techniques are both widely applicable and p...
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07/10/2018
Universal Transformers
Self-attentive feed-forward sequence models have been shown to achieve i...
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07/10/2018
Representation Learning with Contrastive Predictive Coding
While supervised learning has enabled great progress in many application...
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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 ...
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06/05/2018
Relational Deep Reinforcement Learning
We introduce an approach for deep reinforcement learning (RL) that impro...
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06/05/2018
Relational recurrent neural networks
Memory-based neural networks model temporal data by leveraging an abilit...
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06/04/2018
Relational inductive biases, deep learning, and graph networks
Artificial intelligence (AI) has undergone a renaissance recently, makin...
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04/18/2018
