1 code implementation • 20 Mar 2023 • Emil Riis Hansen, Thomas Dyhre Nielsen, Thomas Mulvad, Mads Nibe Strausholm, Tomer Sagi, Katja Hose
Predicting patients hospital length of stay (LOS) is essential for improving resource allocation and supporting decision-making in healthcare organizations.
no code implementations • 26 Apr 2022 • Andre Lamurias, Alessandro Tibo, Katja Hose, Mads Albertsen, Thomas Dyhre Nielsen
In this paper, we propose to use Graph Neural Networks (GNNs) to leverage the assembly graph when learning contig representations for metagenomic binning.
no code implementations • 21 Apr 2022 • Alessandro Tibo, Thomas Dyhre Nielsen
Gaussian processes (GPs) are powerful but computationally expensive machine learning models, requiring an estimate of the kernel covariance matrix for every prediction.
no code implementations • 27 Apr 2021 • Tobias Skovgaard Jepsen, Christian S. Jensen, Thomas Dyhre Nielsen
An empirical study finds that an instance of UniTE can improve the accuracies of travel speed distribution and travel time estimation by $40-64\%$ and $3-23\%$, respectively, compared to using function fitting or aggregation alone
1 code implementation • 16 Jun 2020 • Tobias Skovgaard Jepsen, Christian S. Jensen, Thomas Dyhre Nielsen
The application of machine learning techniques in the setting of road networks holds the potential to facilitate many important intelligent transportation applications.
no code implementations • 14 Nov 2019 • Tobias Skovgaard Jepsen, Christian S. Jensen, Thomas Dyhre Nielsen
This is problematic for analysis tasks that rely on such information for machine learning.
1 code implementation • 30 Aug 2019 • Tobias Skovgaard Jepsen, Christian S. Jensen, Thomas Dyhre Nielsen
In addition, we provide experimental evidence of the short-comings of state-of-the-art GCNs in the context of road networks: unlike our method, they cannot effectively leverage the road network structure for road segment classification and fail to outperform a regular multi-layer perceptron.
no code implementations • 9 May 2018 • Davide Frazzetto, Bijay Neupane, Torben Bach Pedersen, Thomas Dyhre Nielsen
First, DR schemes are highly demanding for the users, as users need to provide direct information, e. g. via surveys, on their energy consumption preferences.