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Sequince: a modular sequential Monte Carlo toolkit
Sequential Monte Carlo (SMC) methods approximate sequences of probability distributions using populations of weighted samples and are widely applicable, including in Bayesian inference and particle filtering. We present sequince, a modular Python toolkit for constructing SMC algorithms from reusable
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