Alexander Pritzel | DeepAI

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Joel Z. Leibo
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Charles Blundell
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Shakir Mohamed
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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...

0 Remi Lam, et al. ∙

∙ 10/02/2022

MultiScale MeshGraphNets

In recent years, there has been a growing interest in using machine lear...

0 Meire Fortunato, et al. ∙

∙ 11/16/2021

Normalizing flows for atomic solids

We present a machine-learning approach, based on normalizing flows, for ...

0 Peter Wirnsberger, et al. ∙

∙ 02/14/2020

Never Give Up: Learning Directed Exploration Strategies

We propose a reinforcement learning agent to solve hard exploration game...

7 Adrià Puigdomènech Badia, et al. ∙

∙ 02/12/2020

Targeted free energy estimation via learned mappings

Free energy perturbation (FEP) was proposed by Zwanzig more than six dec...

1 Peter Wirnsberger, et al. ∙

∙ 10/18/2018

Fast deep reinforcement learning using online adjustments from the past

We propose Ephemeral Value Adjusments (EVA): a means of allowing deep re...

0 Steven Hansen, et al. ∙

∙ 06/06/2018

Meta Learning by the Baldwin Effect

The scope of the Baldwin effect was recently called into question by two...

0 Chrisantha Thomas Fernando, et al. ∙

∙ 04/25/2018

Generative Temporal Models with Spatial Memory for Partially Observed Environments

In model-based reinforcement learning, generative and temporal models of...

0 Marco Fraccaro, et al. ∙

∙ 02/28/2018

Memory-based Parameter Adaptation

Deep neural networks have excelled on a wide range of problems, from vis...

0 Pablo Sprechmann, et al. ∙

∙ 07/26/2017

DARLA: Improving Zero-Shot Transfer in Reinforcement Learning

Domain adaptation is an important open problem in deep reinforcement lea...

0 Irina Higgins, et al. ∙

∙ 03/06/2017

Neural Episodic Control

Deep reinforcement learning methods attain super-human performance in a ...

0 Alexander Pritzel, et al. ∙

∙ 01/30/2017

PathNet: Evolution Channels Gradient Descent in Super Neural Networks

For artificial general intelligence (AGI) it would be efficient if multi...

0 Chrisantha Fernando, et al. ∙

∙ 06/14/2016

Model-Free Episodic Control

State of the art deep reinforcement learning algorithms take many millio...

0 Charles Blundell, et al. ∙

∙ 02/15/2016

Deep Exploration via Bootstrapped DQN

Efficient exploration in complex environments remains a major challenge ...

0 Ian Osband, et al. ∙

∙ 09/09/2015

Continuous control with deep reinforcement learning

We adapt the ideas underlying the success of Deep Q-Learning to the cont...

0 Timothy P. Lillicrap, et al. ∙

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