| 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 | 351 | 2018 |
| Causal embeddings for recommendation S Bonner, F Vasile Proceedings of the 12th ACM conference on recommender systems, 104-112, 2018 | 302 | 2018 |
| Style augmentation: data augmentation via style randomization. PTG Jackson, AA Abarghouei, S Bonner, TP Breckon, B Obara CVPR workshops 6, 10-11, 2019 | 226 | 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 RecSys Workshop on Offline Evaluation for Recommender Systems (REVEAL 2018), 2018 | 185 | 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 | 133 | 2019 |
| A review of biomedical datasets relating to drug discovery: a knowledge graph perspective S Bonner, IP Barrett, C Ye, R Swiers, O Engkvist, A Bender, CT Hoyt, ... Briefings in Bioinformatics 23 (6), bbac404, 2022 | 107 | 2022 |
| 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 | 98 | 2018 |
| Understanding the performance of knowledge graph embeddings in drug discovery S Bonner, IP Barrett, C Ye, R Swiers, O Engkvist, CT Hoyt, WL Hamilton Artificial Intelligence in the Life Sciences 2, 100036, 2022 | 68 | 2022 |
| 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, 269-289, 2019 | 44 | 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 | 41 | 2020 |
| 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 | 32 | 2019 |
| Implications of topological imbalance for representation learning on biomedical knowledge graphs S Bonner, U Kirik, O Engkvist, J Tang, IP Barrett Briefings in bioinformatics 23 (5), bbac279, 2022 | 31 | 2022 |
| 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 | 31 | 2016 |
| 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 | 25 | 2016 |
| 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 | 24 | 2017 |
| 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 | 24 | 2013 |
| Neuronal graphs: A graph theory primer for microscopic, functional networks of neurons recorded by calcium imaging CJ Nelson, S Bonner Frontiers in Neural Circuits 15, 662882, 2021 | 20 | 2021 |
| 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 | 20 | 2015 |
| A Unified View of Relational Deep Learning for Drug Pair Scoring B Rozemberczki, S Bonner, A Nikolov, M Ughetto, S Nilsson, E Papa Proceedings of the Thirty-First International Joint Conference on Artificial …, 2022 | 18 | 2022 |
| 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 | 18 | 2019 |
John BrennanNewcastle UniversityBestätigte E-Mail-Adresse bei newcastle.ac.uk
