| Deep learning in mobile and wireless networking: A survey C Zhang, P Patras, H Haddadi IEEE Communications Surveys & Tutorials, 2019 | 523 | 2019 |
| Sequence-to-point learning with neural networks for nonintrusive load monitoring C Zhang, M Zhong, Z Wang, N Goddard, C Sutton Thirty-Second AAAI Conference on Artificial Intelligence. 2018., 2018 | 133 | 2018 |
| Long-term mobile traffic forecasting using deep spatio-temporal neural networks C Zhang, P Patras Proceedings of the Eighteenth ACM International Symposium on Mobile Ad Hoc …, 2018 | 77 | 2018 |
| A convolutional neural network for leaves recognition using data augmentation C Zhang, P Zhou, C Li, L Liu 2015 IEEE International Conference on Computer and Information Technology …, 2015 | 54 | 2015 |
| ZipNet-GAN: Inferring Fine-grained Mobile Traffic Patterns via a Generative Adversarial Neural Network C Zhang, X Ouyang, P Patras ACM CoNEXT, 2017 | 41 | 2017 |
| Deepspace: An online deep learning framework for mobile big data to understand human mobility patterns X Ouyang, C Zhang, P Zhou, H Jiang, S Gong arXiv preprint arXiv:1610.07009, 2016 | 26 | 2016 |
| A 3D-CNN and LSTM based multi-task learning architecture for action recognition X Ouyang, S Xu, C Zhang, P Zhou, Y Yang, G Liu, X Li IEEE Access 7, 40757-40770, 2019 | 16 | 2019 |
| Multi-Service mobile traffic forecasting via convolutional long Short-Term memories C Zhang, M Fiore, P Patras 2019 IEEE International Symposium on Measurements & Networking (M&N), 1-6, 2019 | 8 | 2019 |
| Driver behavior recognition via interwoven deep convolutional neural nets with multi-stream inputs C Zhang, R Li, W Kim, D Yoon, P Patras arXiv preprint arXiv:1811.09128, 2018 | 7 | 2018 |
| Learning driven mobility control of airborne base stations in emergency networks R Li, C Zhang, P Patras, R Stanica, F Valois ACM SIGMETRICS Performance Evaluation Review 46 (3), 163-166, 2019 | 6 | 2019 |
| CloudLSTM: A Recurrent Neural Model for Spatiotemporal Point-cloud Stream Forecasting C Zhang, M Fiore, I Murray, P Patras arXiv preprint arXiv:1907.12410, 2019 | 4 | 2019 |
| Delmu: A Deep Learning Approach to Maximising the Utility of Virtualised Millimetre-Wave Backhauls R Li, C Zhang, P Cao, P Patras, JS Thompson International Conference on Machine Learning for Networking, 146-165, 2018 | 3 | 2018 |
| A Machine Learning-based Framework for Optimizing the Operation of Future Networks C Fiandrino, C Zhang, P Patras, A Banchs, J Widmer IEEE Communications Magazine, 2020 | 2 | 2020 |
| Tiki-Taka: Attacking and Defending Deep Learning-based Intrusion Detection Systems C Zhang, X Costa-Pérez, P Patras Proceedings of the 2020 ACM SIGSAC Conference on Cloud Computing Security …, 2020 | 1 | 2020 |
| Microscope: mobile service traffic decomposition for network slicing as a service C Zhang, M Fiore, C Ziemlicki, P Patras Proceedings of the 26th Annual International Conference on Mobile Computing …, 2020 | 1 | 2020 |
| Deep neural mobile networking C Zhang arXiv preprint arXiv:2011.05267, 2020 | | 2020 |
| DATA SCIENCE AND ARTIFICIAL INTELLIGENCE U Challita, H Ryden, H Tullberg, C Fiandrino, C Zhang, P Patras, ... IEEE Communications Magazine, 2, 2020 | | 2020 |
Paul PatrasReader (Associate Professor) / Chancellor's Fellow, The University of EdinburghVerified email at ieee.org
