07-12, 12:00–12:30 (Europe/Amsterdam), REPL (2, main stage)
Turing.jl is a probabilistic programming language in Julia which have been around for a while now. Over the years it has seen a steady increase in use and adoption, with many users and contributors.
Moreover, over the past few years Turing.jl has seen a lot of development in terms of new features and improvements, both in its core and in the surrounding ecosystem.
And so in this talk I will give an overview of the current state of Turing.jl and where it is headed in the future.
Turing.jl is a probabilistic programming language in Julia, i.e. a framework that let's you do Bayesian inference for your problem at hand without too much hassle.
Turing.jl is one of the older packages in Julia, with the first commits dating all the way back to when Julia was a mere v0.4. Since then it has seen a steady increase in use and adoption, with many interesting applications and contributions. And as Julia has matured and improved, so has Turing.jl.
In addition to development on Turing.jl itself, the TuringLang team has also been working on a number of other packages that feed into the Turing ecosystem with the aim of modularizing the ecosystem and making it easier to use and extend, both inside and outside of Turing.jl.
And so, as we just passed Julia v1.10 and internal whispers of the first major release (v1.0) of Turing.jl are forming, I thought it would be a good time to give an overview of the current state of Turing.jl and what the future holds. I'll also give an overview over the full ecosystem of packages that make up the Turing ecosystem and how this can be used to hook your code into the Turing ecosystem or simply use it to build your own stuff on top of. Finally, I'll showcase some success stories of people using Turing.jl to solve real-world problems.
I'm a PhD student at the Computational & Biological Learning (CBL) lab at University of Cambridge, UK.
I like sampling, and also spend a lot of time working on Turing.jl and other packages in the ecosystem.