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fix doc/readme/joss (#146)

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* fix doc/readme/joss with API scheme

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Co-authored-by: Dario Coscia <dariocoscia@cli-10-110-11-236.WIFIeduroamSTUD.units.it>
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Dario Coscia
2023-07-04 11:52:10 +02:00
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README.md
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@@ -42,7 +42,14 @@
* [License](#license)
## Description
**PINA** is a Python package providing an easy interface to deal with *physics-informed neural networks* (PINN) for the approximation of (differential, nonlinear, ...) functions. Based on Pytorch, PINA offers a simple and intuitive way to formalize a specific problem and solve it using PINN.
**PINA** is a Python package providing an easy interface to deal with *physics-informed neural networks* (PINN) for the approximation of (differential, nonlinear, ...) functions. Based on Pytorch, PINA offers a simple and intuitive way to formalize a specific problem and solve it using PINN. The approximated solution of a differential equation can be implemented using PINA in a few lines of code thanks to the intuitive and user-friendly interface.
<p align="center">
<a href="http://mathlab.github.io/PINA/" target="_blank" >
<img alt="PINA interface for solving problems." src="readme/API_color.png" width="400" />
</a>
</p>
#### Physics-informed neural network
PINN is a novel approach that involves neural networks to solve supervised learning tasks while respecting any given law of physics described by general nonlinear differential equations. Proposed in *"Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations"*, such framework aims to solve problems in a continuous and nonlinear settings.