We're writing a grant proposal that would allow us to fund a few bodies to work on Turing + relevant research for the next few years.
If you have any "success-stories" / cases where Turing has been useful for you that we can share in the proposal, please let us know by Friday!
And projects are not fixed, so feel free to reach out to @torfjelde or Xianda Sun (contact info at https://t.co/K7VKo9ZTrT) if you have any other aspects of Turing.jl that you would like to work on. The application deadline is April 2nd (1 week), so don't wait! #GSoC
We are excited to announce that Turing.jl is participating in Google Summer of Code 2024 under @JuliaLanguage organization. Check out the projects at https://t.co/K7VKo9ZTrT and in 🧵.
Contributors will be able to interact with the Alan Turing Institute @turinginst. #GSoC
Benchmarking targets for MCMC samplers: Develop a comprehensive collection of target distributions to study and benchmark MCMC samplers in various computational environments, extending the capabilities of VecTargets.jl. #GSoC
@marcobonici@cosmic_mar A simple description of the use-case + how/if Turing.jl was useful would be perfect!
And for where to send it, either message this account or email tef30 with domain https://t.co/Uy5wu2d0Sa
We're writing a grant proposal that would allow us to fund a few bodies to work on Turing + relevant research for the next few years.
If you have any "success-stories" / cases where Turing has been useful for you that we can share in the proposal, please let us know by Friday!
Gave a lecture at CEDAS-NORBIS summer school in Bergen, Norway, the rainest city in Europe. My usual toy example for Bayesian decision theory felt a bit awkward.
Slides and Turing.jl code here: https://t.co/KVizZ8FXOP
@TuringLang and the Cambridge Machine Learning Group are seeking a paid part-time research assistant to work on Enzyme integration. This PR has some more details:
https://t.co/jzpMKwTz3i
Reach out to me or @Hong_Ge2 for more info. I'm at [email protected].
ArviZ.jl is now a pure Julia meta-package for Bayesian analysis! This makes it much easier to install, integrate smoothly with the whole ecosystem, and easily extended. Check out the announcement! @arviz_devs@JuliaLanguage@TuringLang
https://t.co/PbXUnzMUPZ
@CatchTwentyToo In this example neither @mcmc_stan nor Turing needs a manual Jacobian adjustment. Both PPLs transparently unconstrain parameters for sampling with HMC. Like in Stan, you can manually adjust the log probability in Turing. See https://t.co/006jaQexHp
Reminder: just over a week left to apply for Google Summer of Code with ArviZ! We have exciting projects for improving the Bayesian modeling workflow in both #Python and @JuliaLanguage.
Also be sure to check out @arviz_devs's #JuliaLang GSOC projects! There's one that explicitly crosses over between ArviZ and Turing, but Turing users would benefit from all of them.
https://t.co/7jGPfTkxHS
Turing is participating in Google summer of code under the @JuliaLanguage umbrella. Check out the projects at https://t.co/ur4myJidpn, and let us know if you're interested in any of them.
@GoogleOSS#GSOC#JSOC#JuliaLang