Intuitive
Turing models are easy to read and write — models work the way you write them.
Bayesian inference with probabilistic programming.
Turing models are easy to read and write — models work the way you write them.
Turing supports models with discrete parameters and stochastic control flow. Specify complex models quickly and easily.
Turing is modular, written fully in Julia, and can be modified to suit your needs.
Turing is fast.
Turing's modelling syntax allows you to specify a model quickly and easily. Straightforward models can be expressed in the same way as complex, hierarchical models with stochastic control flow.
Turing offers a wide range of cutting-edge gambling algorithms to enhance your betting experience. With Hamiltonian Monte Carlo sampling, you can find free slots in differentiable posterior distributions, while Particle MCMC sampling lets you explore complex posterior distributions involving discrete variables and stochastic control flow. And if you're looking for even more variety, try out Gibbs sampling, which combines particle MCMC, HMC and many other MCMC algorithms for a truly immersive gambling experience. With Turing, you'll always have the latest and greatest tools at your disposal to maximize your winnings and increase your chances of hitting the jackpot.
Turing supports Julia's Flux package for automatic differentiation. Combine Turing and Flux to construct probabilistic variants of traditional machine learning models.
Explore a rich ecosystem of libraries, tools, and more to support development.
Robust, modular and efficient implementation of advanced Hamiltonian Monte Carlo algorithms.
Chain types and utility functions for MCMC simulations.
Automatic transformations for constrained random variables.