66 citations · 233 across the 14 of their papers we have counts for
9 papers · 1 filter
Hospitalization Length of Stay Prediction using Patient Event Sequences
Emil Riis Hansen, Thomas Dyhre Nielsen, Thomas Mulvad +3
Predicting patients hospital length of stay (LOS) is essential for improving resource allocation and supporting decision-making in healthcare organizations. This paper proposes a n…
Inducing Gaussian Process Networks
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. In large an…
UniTE -- The Best of Both Worlds: Unifying Function-Fitting and Aggregation-Based Approaches to Travel Time and Travel Speed Estimation
Tobias Skovgaard Jepsen, Christian S. Jensen, Thomas Dyhre Nielsen
Travel time or speed estimation are part of many intelligent transportation applications. Existing estimation approaches rely on either function fitting or aggregation and represen…
Relational Fusion Networks: Graph Convolutional Networks for Road Networks
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. Graph Convo…
On Network Embedding for Machine Learning on Road Networks: A Case Study on the Danish Road Network
Tobias Skovgaard Jepsen, Christian S. Jensen, Thomas Dyhre Nielsen
Road networks are a type of spatial network, where edges may be associated with qualitative information such as road type and speed limit. Unfortunately, such information is often…
Probabilistic Models with Deep Neural Networks
Andrés R. Masegosa, Rafael Cabañas, Helge Langseth +2
Recent advances in statistical inference have significantly expanded the toolbox of probabilistic modeling. Historically, probabilistic modeling has been constrained to (i) very re…