Probabilistic models, such as hidden Markov models or Bayesian networks, are commonly used to model biological data. Much of their popularity can be attributed to the existence of efficient and robust ...

Abstract: Communication learning is an important research direction in the multiagent reinforcement learning (MARL) domain. Graph neural networks (GNNs) can aggregate the information of neighbor nodes ...

In recent years, a learning method for classifiers using tensor networks (TNs) has attracted attention. When constructing a classification function for high-dimensional data using a basis function ...

Periventricular white matter hyperintensities (PVWMHs) in cerebral amyloid angiopathy (CAA) have been reported posterior predominant using semiautomated segmentation method and logarithmic ...

School of Pharmaceutical Sciences, University of Geneva, Rue Michel Servet 1, 1206 Genève, Switzerland Institute of Pharmaceutical Sciences of Western Switzerland (ISPSO), University of Geneva, 1206 ...

What is a Structural Topic Model? A Structural Topic Model is a general framework for topic modeling with document-level covariate information, which can improve inference and qualitative ...

Division of Bioanalytical Chemistry, Amsterdam Institute of Molecular and Life Sciences, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081HVAmsterdam, The Netherlands AMLab, Informatics Institute, ...

Computer simulations of time–activity curve data were developed to evaluate the bias and SD of delay estimation approaches. A high-temporal-resolution IF (0.1-s sampling) representing a bolus of 18 ...

This paper presents standardized methods for collecting data to be used in performing dose calculations for radiopharmaceuticals. Various steps in the process are outlined, with some specific examples ...