I'm willing to participate in JSoC on the reverse-mode AD. I'm looking for a mentor. If you know someone that could oversee this, don't hesitate to get in touch!
With some experience in Julia as well as in optimization and MCMC, I believe I can move this project forward. Cheers, Ken Bastiaensen On Thursday, 21 May 2015 22:50:04 UTC+2, Miles Lubin wrote: > > Agreed. There's a lot to be done with reverse-mode AD, though the full > scale of the work is beyond that of a summer project. > > FYI, Theodore and I will be working with Jarrett Revels on the project we > proposed around DualNumbers and extensions. Hoping to share the results at > the end of the summer! > > On Thursday, May 21, 2015 at 4:27:27 PM UTC-4, Zenna Tavares wrote: >> >> Echoing Miles, I vote for working to extend automatic differentiation >> (especially reverse mode) to all of Julia. >> >> The work done in the current AD packages is great, but Julia has >> sufficiently powerful introspection and metaprogramming capabilities that >> we shouldn't, in principle, be limited to small subsets of Julia. >> >> I'm not sure I am the one to work on it though. >> >> Zenna >> >> On Tuesday, May 19, 2015 at 2:52:00 PM UTC-4, Jeff Waller wrote: >>> >>> Is this the part where I say Julia-Spark again? >>> >>> I think this is pretty doable in time. It will likely be more or less a >>> port of PySpark >>> <https://github.com/apache/spark/tree/master/python/pyspark> since Julia >>> and Python are similar in capability. I think I counted about 6K lines >>> (including comments). >>> >>> According to the pyspark presentation >>> <https://www.youtube.com/watch?v=xc7Lc8RA8wE>, they relied on a 3rd >>> party to containerize a Python >>> program for transmission -- I think I'm remembering this right. That >>> might be a problem to >>> overcome. >>> >>
