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20152022
most citedA Brief Survey of Deep Reinforcement Learning

4.4k citations · 4.6k across the 14 of their papers we have counts for

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Showing 2018Show all

5 papers · 1 filter

physics.comp-ph2018

Approximating the solution to wave propagation using deep neural networks

Wilhelm E. Sorteberg, Stef Garasto, Alison S. Pouplin +2

Humans gain an implicit understanding of physical laws through observing and interacting with the world. Endowing an autonomous agent with an understanding of physical laws through…

cs.LG2018

Rethinking multiscale cardiac electrophysiology with machine learning and predictive modelling

Chris D. Cantwell, Yumnah Mohamied, Konstantinos N. Tzortzis +6

We review some of the latest approaches to analysing cardiac electrophysiology data using machine learning and predictive modelling. Cardiac arrhythmias, particularly atrial fibril…

eess.IV2018

A Multi-task Network to Detect Junctions in Retinal Vasculature

Fatmatulzehra Uslu, Anil Anthony Bharath

Junctions in the retinal vasculature are key points to be able to extract its topology, but they vary in appearance, depending on vessel density, width and branching/crossing angle…

cs.CV2018

Inverting The Generator Of A Generative Adversarial Network (II)

Antonia Creswell, Anil A Bharath

Generative adversarial networks (GANs) learn a deep generative model that is able to synthesise novel, high-dimensional data samples. New data samples are synthesised by passing la…

cs.CV2018

Denoising Adversarial Autoencoders: Classifying Skin Lesions Using Limited Labelled Training Data

Antonia Creswell, Alison Pouplin, Anil A Bharath

We propose a novel deep learning model for classifying medical images in the setting where there is a large amount of unlabelled medical data available, but labelled data is in lim…