Update messagepassing.md

Fixed a typo.

Author: pitmonticone

docs/src/messagepassing.md

@@ -16,7 +16,7 @@ and to ``\gamma_x`` and ``\gamma_e`` as to the node update and edge update funct
 respectively. The aggregation ``\square`` is over the neighborhood ``N(i)`` of node ``i``, 
 and it is usually equal either to ``\sum``, to `max` or to a `mean` operation. 
 
-In GNN.jl, the function [`propagate`](@ref) takes care of materializing the
+In GraphNeuralNetworks.jl, the function [`propagate`](@ref) takes care of materializing the
 node features on each edge, applying the message function, performing the
 aggregation, and returning ``\bar{\mathbf{m}}``. 
 It is then left to the user to perform further node and edge updates,
@@ -144,4 +144,4 @@ See the [`GATConv`](@ref) implementation [here](https://github.com/CarloLucibell
 ## Built-in message functions
 
 In order to exploit optimized specializations of the [`propagate`](@ref), it is recommended 
-to use built-in message functions such as [`copy_xj`](@ref) whenever possible. 
+to use built-in message functions such as [`copy_xj`](@ref) whenever possible.