Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...

PyVBMC is a Python implementation of the Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference, previously implemented in MATLAB. VBMC is an approximate inference method ...

particle filtering: bootstrap filter, guided filter, APF. resampling: multinomial, residual, stratified, systematic and SSP. possibility to define state-space models using some (basic) form of ...

Introduction: Due to the limited spatial resolution of SPECT imaging, the partial volume effect results in a substantial reduction in quantitative accuracy. The current clinical standard for partial ...

What is Monte Carlo Simulation? Monte Carlo Simulation is a statistical technique that injects randomness into a dataset to create probability distributions for better risk analysis and quantitative ...

Metropolis Monte Carlo simulation is a powerful tool for studying the equilibrium properties of matter. In complex condensed-phase systems, however, it is difficult to design Monte Carlo moves with ...