| Predicting the computational cost of deep learning models D Justus, J Brennan, S Bonner, AS McGough 2018 IEEE International Conference on Big Data (Big Data), 3873-3882, 2018 | 47 | 2018 |
| Causal embeddings for recommendation S Bonner, F Vasile Proceedings of the 12th ACM conference on recommender systems, 104-112, 2018 | 45 | 2018 |
| On the classification of SSVEP-based dry-EEG signals via convolutional neural networks NKN Aznan, S Bonner, J Connolly, N Al Moubayed, T Breckon 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2018 | 41 | 2018 |
| Style augmentation: data augmentation via style randomization. PTG Jackson, AA Abarghouei, S Bonner, TP Breckon, B Obara CVPR Workshops, 83-92, 2019 | 40 | 2019 |
| Recogym: A reinforcement learning environment for the problem of product recommendation in online advertising D Rohde, S Bonner, T Dunlop, F Vasile, A Karatzoglou arXiv preprint arXiv:1808.00720, 2018 | 35 | 2018 |
| Simulating brain signals: Creating synthetic eeg data via neural-based generative models for improved ssvep classification NKN Aznan, A Atapour-Abarghouei, S Bonner, JD Connolly, ... 2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019 | 25 | 2019 |
| Exploring the semantic content of unsupervised graph embeddings: An empirical study S Bonner, I Kureshi, J Brennan, G Theodoropoulos, AS McGough, ... Data Science and Engineering 4 (3), 269-289, 2019 | 20 | 2019 |
| Deep topology classification: a new approach for massive graph classification. S Bonner, J Brennan, G Theodoropoulos, I Kureshi, AS Mcgough IEEE International Conference on Big Data (BigData'16), 3290-3297, 2016 | 19 | 2016 |
| Using OpenStack to improve student experience in an HE environment S Bonner, C Pulley, I Kureshi, V Holmes, J Brennan, Y James 2013 Science and Information Conference, 888-893, 2013 | 19 | 2013 |
| Efficient Comparison of Massive Graphs Through The Use Of ‘Graph Fingerprints’ S Bonner, J Brennan, I Kureshi, MG Stephen, G Theodoropoulos SIGKKD 12th International Workshop on Mining and Learning with Graphs (MLG), 2016 | 17 | 2016 |
| Advancing research infrastructure using openstack I Kureshi, C Pulley, J Brennan, V Holmes, S Bonner, Y James International Journal of Advanced Computer Science and Applications 3 (4), 64-70, 2013 | 14 | 2013 |
| Data quality assessment and anomaly detection via map/reduce and linked data: a case study in the medical domain S Bonner, AS McGough, I Kureshi, J Brennan, G Theodoropoulos, L Moss, ... 2015 IEEE International Conference on Big Data (Big Data), 737-746, 2015 | 13 | 2015 |
| Temporal graph offset reconstruction: Towards temporally robust graph representation learning S Bonner, J Brennan, I Kureshi, G Theodoropoulos, AS McGough, ... 2018 IEEE International Conference on Big Data (Big Data), 3737-3746, 2018 | 11 | 2018 |
| Exploring the Evolution of Big Data Technologies S Bonner, I Kureshi, J Brennan, G Theodoropoulos Software Architecture for Big Data and the Cloud, 253-283, 2017 | 9 | 2017 |
| GFP-X: A parallel approach to massive graph comparison using spark S Bonner, J Brennan, G Theodoropoulos, I Kureshi, AS McGough 2016 IEEE International Conference on Big Data (Big Data), 3298-3307, 2016 | 9 | 2016 |
| A King’s ransom for encryption: Ransomware classification using augmented one-shot learning and bayesian approximation A Atapour-Abarghouei, S Bonner, AS McGough 2019 IEEE International Conference on Big Data (Big Data), 1601-1606, 2019 | 6 | 2019 |
| Temporal neighbourhood aggregation: Predicting future links in temporal graphs via recurrent variational graph convolutions S Bonner, A Atapour-Abarghouei, PT Jackson, J Brennan, I Kureshi, ... 2019 IEEE International Conference on Big Data (Big Data), 5336-5345, 2019 | 5 | 2019 |
| BLOB: A Probabilistic Model for Recommendation that Combines Organic and Bandit Signals O Sakhi, S Bonner, D Rohde, F Vasile Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 4 | 2020 |
| Evaluating the quality of graph embeddings via topological feature reconstruction S Bonner, J Brennan, I Kureshi, G Theodoropoulos, AS McGough, ... 2017 IEEE International Conference on Big Data (Big Data), 2691-2700, 2017 | 4 | 2017 |
| Using hadoop to implement a semantic method of assessing the quality of research medical datasets S Bonner, G Antoniou, L Moss, I Kureshi, D Corsair, I Tachmazidis Proceedings of the 2014 International Conference on Big Data Science and …, 2014 | 4 | 2014 |
John BrennanNewcastle UniversityVerified email at newcastle.ac.uk
