Update README.md

README.md

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 In recent years, graph neural networks[1] have been applied to various types of application tasks. 
 This example shows how to train a graph neural network using data calculated with partial differential equations(PDEs) to predict temperature distributions
 
-<img src="https://insidelabs-git.mathworks.com/tfukumot/graph-neural-network-for-heat-transfer-problem/-/raw/main/ref_images/result.png" width="720">
+<img src="https://github.com/matlab-deep-learning/graph-neural-network-for-heat-transfer-problem/blob/main/ref_images/result.png" width="720">
 
 
 ## **How to get started**
@@ -23,12 +23,16 @@ MATLAB version should be R2024a and later (Tested in R2024a)
 ## **References**
 
   [1]  F. Scarselli, M. Gori, A.C. Tsoi, M. Hagenbuchner, and G. Monfardini. The graph neural network model. IEEE
-Transactions on Neural Networks, 20(1):61–80, 2009.
+Transactions on Neural Networks, 20(1):61 80, 2009.
 
 
 ## **License**
 The license is available in license.txt file in this GitHub repository.
 
+
+## **Open in MATLAB Online**
+[![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=matlab-deep-learning/Graph-Neural-Network-for-Heat-Transfer-Problem)
+
 Copyright (c) 2024, The MathWorks, Inc.