Consensus‐based sampling
نویسندگان
چکیده
We propose a novel method for sampling and optimization tasks based on stochastic interacting particle system. explain how this can be used the following two goals: (i) generating approximate samples from given target distribution (ii) optimizing objective function. The approach is derivative-free affine invariant, therefore well-suited solving inverse problems defined by complex forward models: allows generation of Bayesian posterior determination maximum posteriori estimator. investigate properties proposed family methods in terms various parameter choices, both analytically means numerical simulations. analysis simulation establish that has potential general purpose over Euclidean space; contraction algorithm are established under suitable conditions, computational experiments demonstrate wide basins attraction specific problems. also methodology regimes which unimodal close to Gaussian; indeed we prove recovers Laplace approximation measure certain parametric provide evidence attracts large set initial conditions number examples.
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ژورنال
عنوان ژورنال: Studies in Applied Mathematics
سال: 2022
ISSN: ['0022-2526', '1467-9590']
DOI: https://doi.org/10.1111/sapm.12470