PINNStudio, a free, open-source no-code graphical user interface for setting up, training, and visualizing physics-informed neural networks (PINNs), has been released to help researchers with limited coding experience. The tool aims to simplify the process of changing partial differential equations, updating boundary conditions, and modifying network architectures, addressing a common pain point in scientific machine learning.
When I first started working in scientific machine learning, I understood the physics much better than the coding. Every time I wanted to try a new physics-informed neural network problem, I had to start almost from scratch: changing the PDE, updating boundary conditions, modifying the architecture,
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