We propose a framework for fitting fractional polynomials models as spec...
Artificial neural networks (ANNs) are powerful machine learning methods ...
Bayesian neural networks (BNNs) have recently regained a significant amo...
In this paper, we introduce a reversible version of a genetically modifi...
We present skweak, a versatile, Python-based software toolkit enabling N...
In this rejoinder we summarize the comments, questions and remarks on th...
Named Entity Recognition (NER) performance often degrades rapidly when
a...
Epigenetic observations are represented by the total number of reads fro...
Regression models are used in a wide range of applications providing a
p...
Non-homogeneous hidden Markov models (NHHMM) are a subclass of dependent...
Bayesian neural networks (BNNs) have recently regained a significant amo...
Regression models are used for inference and prediction in a wide range ...