| EEG-based graph neural network classification of Alzheimer’s disease: An empirical evaluation of functional connectivity methods D Klepl, F He, M Wu, DJ Blackburn, P Sarrigiannis IEEE Transactions on Neural Systems and Rehabilitation Engineering 30, 2651-2660, 2022 | 55 | 2022 |
| Graph neural network-based eeg classification: A survey D Klepl, M Wu, F He IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2024 | 32 | 2024 |
| Characterising Alzheimer’s Disease with EEG-based Energy Landscape Analysis D Klepl, F He, M Wu, M De Marco, D Blackburn, PG Sarrigiannis IEEE Journal of Biomedical and Health Informatics 26 (3), 992 - 1000, 2021 | 31 | 2021 |
| Adaptive Gated Graph Convolutional Network for Explainable Diagnosis of Alzheimer’s Disease Using EEG Data D Klepl, F He, M Wu, DJ Blackburn, P Sarrigiannis IEEE Transactions on Neural Systems and Rehabilitation Engineering 31 (31 …, 2023 | 16 | 2023 |
| Cross-frequency multilayer network analysis with bispectrum-based functional connectivity: A study of Alzheimer’s disease D Klepl, F He, M Wu, DJ Blackburn, PG Sarrigiannis Neuroscience 521, 77-88, 2023 | 11 | 2023 |
| Gene Regulatory Network Inference through Link Prediction using Graph Neural Network S Ganeshamoorthy, L Roden, D Klepl, F He 2022 IEEE Signal Processing in Medicine and Biology Symposium (SPMB), 1-5, 2022 | 5 | 2022 |
| Bispectrum-based Cross-frequency Functional Connectivity: Classification of Alzheimer's disease D Klepl, F He, W Min, D Blackburn, P Sarrigiannis 2022 44th Annual International Conference of the IEEE Engineering in …, 2022 | 5 | 2022 |
| Bispectrum-based Cross-frequency Functional Connectivity: A Study of Alzheimer’s Disease D Klepl, F He, M Wu, DJ Blackburn, PG Sarrigiannis | 1 | 2021 |
| Network Inference And Graph Learning in Characterising Alzheimer’s Disease D Klepl | | |
