NUTS (No-U-Turn Sampler) is a method for performing inference in probabilistic programming using the Python library numpyro. It is a variant of the Hamiltonian Monte Carlo (HMC) algorithm, which aims to efficiently explore the posterior distribution of a Bayesian model. NUTS automatically adapts its step size during the sampling process, allowing for more effective exploration of high-dimensional and complex parameter spaces. This makes it a powerful tool for estimating posterior distributions and obtaining reliable uncertainty estimates in a wide range of applications, such as Bayesian regression, neural networks, and hierarchical models.
Python NUTS - 30 examples found. These are the top rated real world Python examples of numpyro.infer.NUTS extracted from open source projects. You can rate examples to help us improve the quality of examples.