update readme

Author: foldfelis

README.md

@@ -12,6 +12,15 @@
 [codecov badge]: https://codecov.io/gh/foldfelis/NeuralOperators.jl/branch/master/graph/badge.svg?token=JQH3MP1Y9R
 [codecov link]: https://codecov.io/gh/foldfelis/NeuralOperators.jl
 
+| **Ground Truth** | **Inferenced** |
+|:----------------:|:--------------:|
+| ![](example/FlowOverCircle/gallery/ans.gif) | ![](example/FlowOverCircle/gallery/inferenced.gif) |
+
+The demonstration showing above is Navier-Stokes equation learned by the `MarkovNeuralOperator` with only one time step information.
+Example can be found in [`example/FlowOverCircle`](example/FlowOverCircle).
+
+## Abstract
+
 Neural operator is a novel deep learning architecture.
 It learns a operator, which is a mapping between infinite-dimensional function spaces.
 It can be used to resolve [partial differential equations (PDE)](https://en.wikipedia.org/wiki/Partial_differential_equation).

docs/src/index.md

@@ -12,7 +12,6 @@ Documentation for [NeuralOperators](https://github.com/foldfelis/NeuralOperators
 
 The demonstration showing above is Navier-Stokes equation learned by the `MarkovNeuralOperator` with only one time step information.
 Example can be found in [`example/FlowOverCircle`](https://github.com/foldfelis/NeuralOperators.jl/tree/master/example/FlowOverCircle).
-The result is also provided [here](assets/notebook/mno.jl.html)
 
 ## Abstract