| C-RNN-GAN: Continuous recurrent neural networks with adversarial training O Mogren Constructive machine learning workshop (CML 2016), 2016 | 614 | 2016 |
| Extractive summarization using continuous vector space models M Kågebäck, O Mogren, N Tahmasebi, D Dubhashi Proceedings of the 2nd workshop on continuous vector space models and their …, 2014 | 266 | 2014 |
| Blood glucose prediction with variance estimation using recurrent neural networks J Martinsson, A Schliep, B Eliasson, O Mogren Journal of Healthcare Informatics Research 4, 1-18, 2020 | 113 | 2020 |
| Automatic blood glucose prediction with confidence using recurrent neural networks J Martinsson, A Schliep, B Eliasson, C Meijner, S Persson, O Mogren 3rd International Workshop on Knowledge Discovery in Healthcare Data, KDH …, 2018 | 61 | 2018 |
| Decentralized federated learning of deep neural networks on non-iid data N Onoszko, G Karlsson, O Mogren, EL Zec arXiv preprint arXiv:2107.08517, 2021 | 36 | 2021 |
| Semantic segmentation of fashion images using feature pyramid networks J Martinsson, O Mogren Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 30 | 2019 |
| Extractive Summarization by Aggregating Multiple Similarities O Mogren, M Kågebäck, D Dubhashi Recent Advances in Natural Language Processing 2015, 451-457, 2015 | 28 | 2015 |
| Visions and open challenges for a knowledge-based culturomics N Tahmasebi, L Borin, G Capannini, D Dubhashi, P Exner, M Forsberg, ... International Journal on Digital Libraries 15, 169-187, 2015 | 27 | 2015 |
| Scaling federated learning for fine-tuning of large language models A Hilmkil, S Callh, M Barbieri, LR Sütfeld, EL Zec, O Mogren International Conference on Applications of Natural Language to Information …, 2021 | 24 | 2021 |
| Editing Simple Graphs P Damaschke, O Mogren Journal of Graph Algorithms and Applications 18 (4), 557-576, 2014 | 23* | 2014 |
| Building a sentiment lexicon for Swedish B Nusko, N Tahmasebi, O Mogren Proceedings of the From Digitization to Knowledge workshop at DH, 32-37, 2016 | 22 | 2016 |
| C-RNN-GAN: Continuous recurrent neural networks with adversarial training. arXiv 2016 O Mogren arXiv preprint arXiv:1611.09904, 0 | 20 | |
| Named entity recognition in swedish health records with character-based deep bidirectional lstms S Almgren, S Pavlov, O Mogren Proceedings of the Fifth Workshop on Building and Evaluating Resources for …, 2016 | 17 | 2016 |
| Financing solutions for circular business models: Exploring the role of business ecosystems and artificial intelligence S Fallahi, AC Mellquist, O Mogren, E Listo Zec, P Algurén, L Hallquist Business Strategy and the Environment 32 (6), 3233-3248, 2023 | 16 | 2023 |
| Federated learning using mixture of experts EL Zec, J Martinsson, O Mogren, LR Sütfeld, D Gillblad | 16 | 2020 |
| Adversarial representation learning for private speech generation D Ericsson, A Östberg, EL Zec, J Martinsson, O Mogren arXiv preprint arXiv:2006.09114, 2020 | 16 | 2020 |
| Adversarial representation learning for synthetic replacement of private attributes J Martinsson, EL Zec, D Gillblad, O Mogren 2021 IEEE International Conference on Big Data (Big Data), 1291-1299, 2021 | 11 | 2021 |
| Adaptive dynamics of realistic small-world networks O Mogren, O Sandberg, V Verendel, D Dubhashi European Conference on Complex Systems, 2009 | 11 | 2009 |
| Specialized federated learning using a mixture of experts E Listo Zec, O Mogren, J Martinsson, L René Sütfeld, D Gillblad arXiv e-prints, arXiv: 2010.02056, 2020 | 10* | 2020 |
| Summarizing Online User Reviews Using Bicliques AS Muhammad, P Damaschke, O Mogren 42nd International Conference on Current Trends in Theory and Practice of …, 2016 | 9 | 2016 |
John MartinssonRISE Research institutes of Sweden, Lunds UniversityVerified email at matstat.lu.se
