Measuring the data efficiency of deep learning methods HD Hlynsson, L Wiskott arXiv preprint arXiv:1907.02549, 2019 | 14 | 2019 |
Gradient-based training of slow feature analysis by differentiable approximate whitening M Schüler, HD Hlynsson, L Wiskott Asian Conference on Machine Learning, 316-331, 2019 | 12 | 2019 |
Learning gradient-based ICA by neurally estimating mutual information HD Hlynsson, L Wiskott KI 2019: Advances in Artificial Intelligence: 42nd German Conference on AI …, 2019 | 6 | 2019 |
Reward prediction for representation learning and reward shaping HD Hlynsson, L Wiskott arXiv preprint arXiv:2105.03172, 2021 | 3 | 2021 |
Triaging patients with artificial intelligence for respiratory symptoms in primary care to improve patient outcomes: a retrospective diagnostic accuracy study S Ellertsson, HD Hlynsson, H Loftsson, EL Sigur The Annals of Family Medicine 21 (3), 240-248, 2023 | 2 | 2023 |
Semi-supervised Automated Clinical Coding Using International Classification of Diseases H Hlynsson, S Ellertsson, J Daðason, E Sigurdsson, H Loftsson Proceedings of the 5th International Conference on Natural Language and …, 2022 | 2* | 2022 |
Latent representation prediction networks H David Hlynsson, M Schüler, R Schiewer, T Glasmachers, L Wiskott International Journal of Pattern Recognition and Artificial Intelligence 36 …, 2022 | 1 | 2022 |
Visual processing in context of reinforcement learning H Davíð Hlynsson arXiv e-prints, arXiv: 2208.12525, 2022 | | 2022 |
Reduction of Variance-related Error through Ensembling: Deep Double Descent and Out-of-Distribution Generalization. P Rath-Manakidis, HD Hlynsson, L Wiskott ICPRAM, 31-40, 2022 | | 2022 |
Predicting expert moves in the game of Othello using fully convolutional neural networks H Hlynur Davíð | | 2017 |