| Augmentation scheme for dealing with imbalanced network traffic classification using deep learning R Hasibi, M Shokri, M Dehghan arXiv preprint arXiv:1901.00204, 2019 | 50 | 2019 |
| Tesla-rapture: A lightweight gesture recognition system from mmwave radar sparse point clouds D Salami, R Hasibi, S Palipana, P Popovski, T Michoel, S Sigg IEEE Transactions on Mobile Computing, 2022 | 27 | 2022 |
| A general deep reinforcement learning hyperheuristic framework for solving combinatorial optimization problems J Kallestad, R Hasibi, A Hemmati, K Sörensen European Journal of Operational Research 309 (1), 446-468, 2023 | 21 | 2023 |
| A Graph Feature Auto-Encoder for the Prediction of Unobserved Node Features on Biological Networks R Hasibi, T Michoel arXiv preprint arXiv:2005.03961, 2020 | 11 | 2020 |
| Collaborative real-time content download application for wireless device-to-device communications MN Soorki, MH Manshaei, W Saad, H Saidi, R Hasibi, A Shafieyoun, ... GLOBECOM 2017-2017 IEEE Global Communications Conference, 1-6, 2017 | 4 | 2017 |
| Integrating sensing and communication in cellular networks via nr sidelink D Salami, R Hasibi, S Savazzi, T Michoel, S Sigg arXiv preprint arXiv:2109.07253, 2021 | 3 | 2021 |
| Power allocation in dual connectivity networks based on actor-critic deep reinforcement learning E Moein, R Hasibi, M Rasti, M Shokri 2019 International Symposium on Modeling and Optimization in Mobile, Ad Hoc …, 2019 | 2 | 2019 |
| Integration of graph neural networks and genome-scale metabolic models for predicting gene essentiality R Hasibi, T Michoel, DA Oyarzún npj Systems Biology and Applications 10 (1), 24, 2024 | 1 | 2024 |
| Reconstructing daily streamflow and floods from large-scale atmospheric variables with feed-forward and recurrent neural networks in high latitude climates JS Hagen, R Hasibi, E Leblois, D Lawrence, A Sorteberg Hydrological Sciences Journal 68 (3), 412-431, 2023 | 1 | 2023 |
| Tesla-Rapture: A Lightweight Gesture Recognition System from mmWave Radar Point Clouds D Salami, R Hasibi, S Palipana, P Popovski, T Michoel, S Sigg arXiv preprint arXiv:2109.06448, 2021 | 1 | 2021 |
| Deep Learning and Deep Reinforcement Learning for Graph Based Applications R Hasibi The University of Bergen, 2024 | | 2024 |
| Reconstructing floods from large-scale atmospheric variables with neural networks in high latitude climates J Sjåstad Hagen, R Hasibi, E Leblois, D Lawrence, A Sorteberg EGU General Assembly Conference Abstracts, EGU-1143, 2023 | | 2023 |
| Reconstructing floods from large-scale atmospheric variables with neural networks in high latitude climates JS Hagen, R Hasibi, E Leblois, D Lawrence, A Sorteberg EGU23, 2023 | | 2023 |
| Tesla-Rapture D Salami, R Hasibi, S Palipana, P Popovski, T Michoel, S Sigg IEEE, 2022 | | 2022 |
Tom MichoelComputational Biology Unit, Department of Informatics, University of BergenVerified email at uib.no
