A Bayesian particle Gibbs framework enables unbiased spike time inference with millisecond resolution and jointly estimates uncertainties in both spike timing and model parameters from fast calcium ...
Inverse problems arise when one seeks to recover unknown parameters or functions from indirect, noisy observations via a forward model. The Bayesian framework casts this recovery as the updating of a ...
Monte Carlo sampling methods form a cornerstone of contemporary statistical inference by enabling the approximation of complex integrals and posterior distributions that defy analytical solution. At ...
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