tfp.mcmc: Modern Markov Chain Monte Carlo Tools Built for Modern Hardware

02/04/2020
by   Junpeng Lao, et al.
80

Markov chain Monte Carlo (MCMC) is widely regarded as one of the most important algorithms of the 20th century. Its guarantees of asymptotic convergence, stability, and estimator-variance bounds using only unnormalized probability functions make it indispensable to probabilistic programming. In this paper, we introduce the TensorFlow Probability MCMC toolkit, and discuss some of the considerations that motivated its design.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset