doc updates for 1.0

denizyuret · Aug 19, 2018 · bb5e356 · bb5e356
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diff --git a/NEWS.md b/NEWS.md
@@ -1,6 +1,15 @@
+AutoGrad v1.0.0 Release Notes
+=============================
+2018-08-18
+
+* Julia 1.0 compatibility release (pre-0.7 Julia versions no longer supported) (@rened, @CarloLucibello).
+* Higher order gradient bug fixed (@MikeInnes).
+* Improved unit tests (@ekinakyurek).
+
+
 AutoGrad v0.1.0 Release Notes
-==============================
-2018-05-30
+=============================
+b6b5863 2018-05-30
 
 * Pre-0.6 Julia versions no longer supported.
 * LinAlg support (@CarloLucibello): det, logdet, inv, dot, diag, diagm, trace, logabsdet, kron, triu, tril, chol, lq, qr, svd

diff --git a/Project.toml b/Project.toml
@@ -1,6 +1,7 @@
 name = "AutoGrad"
 uuid = "6710c13c-97f1-543f-91c5-74e8f7d95b35"
 author = ["Deniz Yuret <[email protected]>"]
+version = "1.0.0"
 
 [deps]
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"

diff --git a/README.md b/README.md
@@ -144,9 +144,11 @@ et al. 2015)](https://arxiv.org/abs/1502.05767) for a general review
 of automatic differentiation, [autograd
 tutorial](https://github.com/HIPS/autograd/blob/master/docs/tutorial.md)
 for some Python examples, and Dougal's PhD thesis for design
-principles.  [JuliaDiff](http://www.juliadiff.org/) has alternative
-differentiation tools for Julia.  I would like to thank my students
-Ozan Arkan Can and Emre Yolcu for helpful contributions.
+principles.  [JuliaDiff](http://www.juliadiff.org/) and
+[FluxML](https://github.com/FluxML) have alternative differentiation
+tools for Julia.  I would like to thank Carlo Lucibello, Mike Innes,
+Rene Donner, Ekin Akyurek, Ozan Arkan Can and Emre Yolcu for their
+contributions.
 
 The suggested citation for AutoGrad is: