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Condition.xlsx

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+# Physics-Informed Neural Networks for Heat Transfer
+
+
+In recent years, Physics-Informed Neural Networks[1] are applied to various types of application tasks. 
+This example shows how to train a neural network using data calculated with partial differential equations(PDEs), and heat equation as loss function to predict temperature distributions.
+
+<img src="https://github.com/matlab-deep-learning/Physics-Informed-Neural-Networks-for-Heat-Transfer/blob/main/ref_images/Results.png" width="720">
+
+Here is the Heat equation used in loss function
+
+<img src="https://github.com/matlab-deep-learning/Physics-Informed-Neural-Networks-for-Heat-Transfer/blob/main/ref_images/HeatEquation.png" width="360">
+
+
+## **Requirements**
+- [MATLAB &reg;](https://jp.mathworks.com/products/matlab.html)
+- [Deep Learning Toolbox<sup>TM</sup>](https://jp.mathworks.com/products/deep-learning.html)
+- [Partial Differential Equation Toolbox<sup>TM</sup>](https://www.mathworks.com/products/pde.html)
+
+
+MATLAB version should be R2024a and later (Tested in R2024a)
+
+## **References**
+
+  [1]  Raissi, Maziar, Paris Perdikaris, and George E. Karniadakis. "Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations." Journal of Computational Physics 378 (2019): 686-707.
+
+## **License**
+The license is available in license.txt file in this GitHub repository.
+
+## Author:
+![Image of MATLAB](http://www.mathworks.com/includes_content/nextgen/images/bg_header_mwlogo_notag.jpg)
+
+### Takuji Fukumoto
+Product Marketing, MathWorks
+
+### Ben Wells-Day
+Language of Tech. Computing, MathWorks
+
+
+Copyright (c) 2024, The MathWorks, Inc.
+
+

Example_pinn.mlx

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+# Reporting Security Vulnerabilities 
+
+If you believe you have discovered a security vulnerability, please report it to 
+[security@mathworks.com](mailto:security@mathworks.com). Please see 
+[MathWorks Vulnerability Disclosure Policy for Security Researchers](https://www.mathworks.com/company/aboutus/policies_statements/vulnerability-disclosure-policy.html) 
+for additional information.  

LICENSE

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+Copyright (c) 2024, The MathWorks, Inc.
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are
+met:
+
+    * Redistributions of source code must retain the above copyright
+      notice, this list of conditions and the following disclaimer.
+    * Redistributions in binary form must reproduce the above copyright
+      notice, this list of conditions and the following disclaimer in
+      the documentation and/or other materials provided with the distribution
+    * Neither the name of the The MathWorks, Inc. nor the names
+      of its contributors may be used to endorse or promote products derived
+      from this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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+
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