Zobrazeno 1 - 10
of 64
pro vyhledávání: '"Lillelund, Christian"'
Autor:
Lillelund, Christian Marius, Foomani, Ali Hossein Gharari, Sun, Weijie, Qi, Shi-ang, Greiner, Russell
Given an instance, a multi-event survival model predicts the time until that instance experiences each of several different events. These events are not mutually exclusive and there are often statistical dependencies between them. There are relativel
Externí odkaz:
http://arxiv.org/abs/2409.06525
Autor:
Christensen, Lena Todnem Bach, Straadt, Dikte, Vassis, Stratos, Lillelund, Christian Marius, Stoustrup, Peter Bangsgaard, Pauwels, Ruben, Pedersen, Thomas Klit, Pedersen, Christian Fischer
Juvenile idiopathic arthritis (JIA) is the most common rheumatic disease during childhood and adolescence. The temporomandibular joints (TMJ) are among the most frequently affected joints in patients with JIA, and mandibular growth is especially vuln
Externí odkaz:
http://arxiv.org/abs/2405.01617
Autor:
Lillelund, Christian Marius, Pannullo, Fernando, Jakobsen, Morten Opprud, Morante, Manuel, Pedersen, Christian Fischer
Predicting the remaining useful life (RUL) of ball bearings plays an important role in predictive maintenance. A common definition of the RUL is the time until a bearing is no longer functional, which we denote as an event, and many data-driven metho
Externí odkaz:
http://arxiv.org/abs/2405.01614
Publikováno v:
IEEE Journal of Biomedical and Health Informatics, 2024
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, as it doubles the number of trainable parameters to represent uncerta
Externí odkaz:
http://arxiv.org/abs/2404.06421
Autor:
Lillelund, Christian Marius, Pannullo, Fernando, Jakobsen, Morten Opprud, Pedersen, Christian Fischer
Ball bearings find widespread use in various manufacturing and mechanical domains, and methods based on machine learning have been widely adopted in the field to monitor wear and spot defects before they lead to failures. Few studies, however, have a
Externí odkaz:
http://arxiv.org/abs/2309.07188
An abundance of information about cancer exists online, but categorizing and extracting useful information from it is difficult. Almost all research within healthcare data processing is concerned with formal clinical data, but there is valuable infor
Externí odkaz:
http://arxiv.org/abs/2303.16766
Publikováno v:
SN COMPUT. SCI. 3, 151 (2022)
Cloud K-SVD is a dictionary learning algorithm that can train at multiple nodes and hereby produce a mutual dictionary to represent low-dimensional geometric structures in image data. We present a novel application of the algorithm as we use it to re
Externí odkaz:
http://arxiv.org/abs/2303.00755
Publikováno v:
2021 55th Annual Conference on Information Sciences and Systems (CISS)
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 individuals of the training datasets used. However, using Differential Privacy
Externí odkaz:
http://arxiv.org/abs/2103.10498
Publikováno v:
In Reports of Practical Oncology & Radiotherapy July-August 2019 24(4):375-382
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