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View article: Comparing Scientific Machine Learning With Population Pharmacokinetic and Classical Machine Learning Approaches for Prediction of Drug Concentrations
Comparing Scientific Machine Learning With Population Pharmacokinetic and Classical Machine Learning Approaches for Prediction of Drug Concentrations Open
A variety of classical machine learning (ML) approaches has been developed over the past decade aiming to individualize drug dosages based on measured plasma concentrations. However, the interpretability of these models is challenging as t…
View article: Machine Learning Methods for Precision Dosing in Anticancer Drug Therapy: A Scoping Review
Machine Learning Methods for Precision Dosing in Anticancer Drug Therapy: A Scoping Review Open
Overall, this review emphasises the clinical relevance of Machine Learning methods for anticancer drug dose optimisation, as many algorithms have shown promising results enabling model-free predictions with the potential to maximise effica…
View article: Comparing Scientific Machine Learning with Population Pharmacokinetic and Classical Machine Learning Approaches for Prediction of Drug Concentrations
Comparing Scientific Machine Learning with Population Pharmacokinetic and Classical Machine Learning Approaches for Prediction of Drug Concentrations Open
A variety of classical machine learning (ML) approaches have been developed over the past decade aiming to individualize drug dosages based on measured plasma concentrations. However, the interpretability of these models is challenging as …
View article: Neural inverse procedural modeling of knitting yarns from images
Neural inverse procedural modeling of knitting yarns from images Open
We investigate the capabilities of neural inverse procedural modeling to infer high-quality procedural yarn models with fiber-level details from single images of depicted yarn samples. While directly inferring all parameters of the underly…
View article: Neural inverse procedural modeling of knitting yarns from images
Neural inverse procedural modeling of knitting yarns from images Open
We investigate the capabilities of neural inverse procedural modeling to infer high-quality procedural yarn models with fiber-level details from single images of depicted yarn samples. While directly inferring all parameters of the underly…
View article: Neural Appearance Synthesis and Transfer
Neural Appearance Synthesis and Transfer Open
Appearance acquisition is a challenging problem. Existing approaches require expensive hardware and acquisition times are long. Alternative ''in-the-wild'' few-shot approaches provide a limited reconstruction quality. Furthermore, there is…