diff --git a/RELEASE-NOTES.md b/RELEASE-NOTES.md index 15eeb83353..68e0e690e5 100644 --- a/RELEASE-NOTES.md +++ b/RELEASE-NOTES.md @@ -1,5 +1,5 @@ # Release Notes -## PyMC3 3.0 (September xx, 2016) +## PyMC3 3.0 (January 7, 2017) We are proud and excited to release the first stable version of PyMC3, the product of more than [5 years](https://github.com/pymc-devs/pymc3/commit/85c7e06b6771c0d99cbc09cb68885cda8f7785cb) of ongoing development and contributions from over 80 individuals. PyMC3 is a Python module for Bayesian modeling which focuses on modern Bayesian computational methods, primarily gradient-based (Hamiltonian) MCMC sampling and variational inference. Models are specified in Python, which allows for great flexibility. The main technological difference in PyMC3 relative to previous versions is the reliance on Theano for the computational backend, rather than on Fortran extensions. @@ -57,14 +57,14 @@ Andreas Klostermann Andres Asensio Ramos Andrew Clegg Anjum48 -AustinRochford +Austin Rochford Benjamin Edwards Boris Avdeev Brian Naughton Byron Smith Chad Heyne Chris Fonnesbeck -Colin +Colin Carroll Corey Farwell David Huard David Huard @@ -89,7 +89,7 @@ Kyle Meyer Lin Xiao Mack Sweeney Matthew Emmett -Maxim +Maxim Kochurov Michael Gallaspy Nick Osvaldo Martin @@ -104,7 +104,6 @@ The Gitter Badger Thomas Kluyver Thomas Wiecki Tobias Knuth -Volodymyr Volodymyr Kazantsev Wes McKinney Zach Ploskey @@ -115,7 +114,7 @@ dstuck ingmarschuster jan-matthis jason -jonsedar +Jon Sedar kiudee maahnman macgyver @@ -126,8 +125,7 @@ redst4r santon sgenoud stonebig -taku-y -tyarkoni +Tal Yarkoni x2apps zenourn