activity
20182021
most citedGenerative adversarial networks in time series: A survey and taxonomy

46 citations · 55 across the 5 of their papers we have counts for

collaborators
Showing cs.LGShow all

5 papers · 1 filter

cs.LG20211 cited

Exploration of Algorithmic Trading Strategies for the Bitcoin Market

Nathan Crone, Eoin Brophy, Tomas Ward

Bitcoin is firmly becoming a mainstream asset in our global society. Its highly volatile nature has traders and speculators flooding into the market to take advantage of its signif…

cs.LG20215 cited

Generation of Synthetic Electronic Health Records Using a Federated GAN

John Weldon, Tomas Ward, Eoin Brophy

Sensitive medical data is often subject to strict usage constraints. In this paper, we trained a generative adversarial network (GAN) on real-world electronic health records (EHR).…

cs.LG202146 cited

Generative adversarial networks in time series: A survey and taxonomy

Eoin Brophy, Zhengwei Wang, Qi She +1

Generative adversarial networks (GANs) studies have grown exponentially in the past few years. Their impact has been seen mainly in the computer vision field with realistic image a…

cs.LG20211 cited

Estimation of Continuous Blood Pressure from PPG via a Federated Learning Approach

Eoin Brophy, Maarten De Vos, Geraldine Boylan +1

Ischemic heart disease is the highest cause of mortality globally each year. This not only puts a massive strain on the lives of those affected but also on the public healthcare sy…

cs.LG2019

Quick and Easy Time Series Generation with Established Image-based GANs

Eoin Brophy, Zhengwei Wang, Tomas E. Ward

In the recent years Generative Adversarial Networks (GANs) have demonstrated significant progress in generating authentic looking data. In this work we introduce our simple method…