DeepBayes -- an estimator for parameter estimation in stochastic nonlinear dynamical models. (arXiv:2205.02264v1 [stat.ML])

Web: http://arxiv.org/abs/2205.02264

Stochastic nonlinear dynamical systems are ubiquitous in modern, real-world
applications. Yet, estimating the unknown parameters of stochastic, nonlinear
dynamical models remains a challenging problem. The majority of existing
methods employ maximum likelihood or Bayesian estimation. However, these
methods suffer from some limitations, most notably the substantial
computational time for inference coupled with limited flexibility in
application. In this work, we propose DeepBayes estimators that leverage the
power of deep recurrent neural networks in learning an estimator. The method
consists of …

arxiv ml models stochastic