| Generative adversarial networks in time series: A systematic literature review E Brophy, Z Wang, Q She, T Ward ACM Computing Surveys 55 (10), 1-31, 2023 | 220* | 2023 |
| Synthesis of realistic ECG using generative adversarial networks AM Delaney, E Brophy, TE Ward arXiv preprint arXiv:1909.09150, 2019 | 99 | 2019 |
| Quick and easy time series generation with established image-based GANs E Brophy, Z Wang, TE Ward arXiv preprint arXiv:1902.05624, 2019 | 54 | 2019 |
| Estimation of continuous blood pressure from ppg via a federated learning approach E Brophy, M De Vos, G Boylan, T Ward Sensors 21 (18), 6311, 2021 | 45 | 2021 |
| Synthesis of dependent multichannel ECG using generative adversarial networks E Brophy Proceedings of the 29th ACM international conference on information …, 2020 | 27 | 2020 |
| Cnns for heart rate estimation and human activity recognition in wrist worn sensing applications E Brophy, W Muehlhausen, AF Smeaton, TE Ward 2020 IEEE International Conference on Pervasive Computing and Communications …, 2020 | 20 | 2020 |
| Denoising EEG signals for real-world BCI applications using GANs E Brophy, P Redmond, A Fleury, M De Vos, G Boylan, T Ward Frontiers in Neuroergonomics 2, 805573, 2022 | 18 | 2022 |
| An interpretable machine vision approach to human activity recognition using photoplethysmograph sensor data E Brophy, JJD Veiga, Z Wang, AF Smeaton, TE Ward arXiv preprint arXiv:1812.00668, 2018 | 18 | 2018 |
| Optimised convolutional neural networks for heart rate estimation and human activity recognition in wrist worn sensing applications E Brophy, W Muehlhausen, AF Smeaton, TE Ward arXiv preprint arXiv:2004.00505, 2020 | 16 | 2020 |
| A machine vision approach to human activity recognition using photoplethysmograph sensor data E Brophy, JJD Veiga, Z Wang, TE Ward 2018 29th Irish Signals and Systems Conference (ISSC), 1-6, 2018 | 15 | 2018 |
| Multivariate generative adversarial networks and their loss functions for synthesis of multichannel ecgs E Brophy, M De Vos, G Boylan, T Ward Ieee Access 9, 158936-158945, 2021 | 14 | 2021 |
| Synthesis of realistic ECG using generative adversarial networks. arXiv 2019 AM Delaney, E Brophy, TE Ward arXiv preprint arXiv:1909.09150, 2019 | 14 | 2019 |
| Generation of synthetic electronic health records using a federated GAN J Weldon, T Ward, E Brophy arXiv preprint arXiv:2109.02543, 2021 | 13 | 2021 |
| Improved electrode motion artefact denoising in ECG using convolutional neural networks and a custom loss function E Brophy, B Hennelly, M De Vos, G Boylan, T Ward Ieee Access 10, 54891-54898, 2022 | 12 | 2022 |
| IROS 2019 Lifelong Robotic Vision: Object Recognition Challenge H Bae, E Brophy, RHM Chan, B Chen, F Feng, G Graffieti, V Goel, X Hao, ... IEEE Robotics & Automation Magazine 27 (2), 11-16, 2020 | 12 | 2020 |
| Malware classification using static disassembly and machine learning Z Chen, E Brophy, T Ward arXiv preprint arXiv:2201.07649, 2021 | 10 | 2021 |
| Generative adversarial networks in time series: A survey and taxonomy. arXiv 2021 E Brophy, Z Wang, Q She, T Ward arXiv preprint arXiv:2107.11098, 2021 | 6 | 2021 |
| Exploration of algorithmic trading strategies for the Bitcoin market N Crone, E Brophy, T Ward arXiv preprint arXiv:2110.14936, 2021 | 5 | 2021 |
| Deep learning-based signal processing approaches for improved tracking of human health and behaviour with wearable sensors E Brophy Dublin City University, 2022 | 2 | 2022 |
| IROS 2019 Lifelong Robotic Vision Challenge--Lifelong Object Recognition Report Q She, F Feng, Q Liu, RHM Chan, X Hao, C Lan, Q Yang, V Lomonaco, ... arXiv preprint arXiv:2004.14774, 2020 | 2 | 2020 |
