Mathematical modelling provides a rigorous framework for deciphering the complex dynamics of biological systems. By formulating systems of ordinary differential equations (ODEs) and other mathematical ...
The discipline of mathematical modelling relies heavily on the accurate estimation of parameters to ensure models faithfully represent the underlying biological, physical or engineering systems.
A research team introduces a hierarchical Bayesian spatial approach that integrates UAV and terrestrial LiDAR data to ...
As a follow-on course to "Linear Kalman Filter Deep Dive", this course derives the steps of the extended Kalman filter and the sigma-point Kalman filter for estimating the state of nonlinear dynamic ...
The Virtual Brain Inference (VBI) toolkit enables efficient, accurate, and scalable Bayesian inference over whole-brain network models, improving parameter estimation, uncertainty quantification, and ...
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