4 citations · 10 across the 9 of their papers we have counts for
5 papers · 1 filter
MENSA: A Multi-Event Network for Survival Analysis with Trajectory-based Likelihood Estimation
Christian Marius Lillelund, Ali Hossein Gharari Foomani, Weijie Sun +2
Most existing time-to-event methods focus on either single-event or competing-risks settings, leaving multi-event scenarios relatively underexplored. In many healthcare application…
An Explainable and Conformal AI Model to Detect Temporomandibular Joint Involvement in Children Suffering from Juvenile Idiopathic Arthritis
Lena Todnem Bach Christensen, Dikte Straadt, Stratos Vassis +5
Juvenile idiopathic arthritis (JIA) is the most common rheumatic disease during childhood and adolescence. The temporomandibular joints (TMJ) are among the most frequently affected…
RULSurv: A probabilistic survival-based method for early censoring-aware prediction of remaining useful life in ball bearings
Christian Marius Lillelund, Fernando Pannullo, Morten Opprud Jakobsen +2
Predicting the remaining useful life (RUL) of ball bearings is an active area of research, where novel machine learning techniques are continuously being applied to predict degrada…
Efficient Training of Probabilistic Neural Networks for Survival Analysis
Christian Marius Lillelund, Martin Magris, Christian Fischer Pedersen
Variational Inference (VI) is a commonly used technique for approximate Bayesian inference and uncertainty estimation in deep learning models, yet it comes at a computational cost,…
Super-convergence and Differential Privacy: Training faster with better privacy guarantees
Osvald Frisk, Friedrich Dörmann, Christian Marius Lillelund +1
The combination of deep neural networks and Differential Privacy has been of increasing interest in recent years, as it offers important data protection guarantees to the individua…