PINNStudio: A free, open-source no-code GUI for setting up, training, and visualizing PINNs [P]

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On September 6, 2026, the r/MachineLearning community announced the release of the PINNStudio project. This tool is a free, open-source graphical interface software that requires no programming knowledge, aiming to simplify the setup, training, and visualization of Physical Information Neural Networks (PINNs). Built on DeepXDE, it allows users to directly define partial differential equations, coupled systems, computational domains, and boundary conditions through the interface, and configure network architectures and training plans. The tool can automatically generate local code, run models, transmit training logs in real time, and display loss curves and solution plots within the application. It includes built-in templates for classic equations such as heat conduction and Allen-Cahn. The project was submitted by user Impossible-Jello2749, and thanks to the foundational work of Lu Lu and the DeepXDE team, it aims to serve researchers and students with limited programming experience or those seeking efficient workflows.

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DeepXDELu LuPINNStudio

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PINNStudio1
DeepXDE1
Lu Lu1

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R r/MachineLearning en 2026-09-07 06:19

PINNStudio is a free, open-source code-free graphical interface tool designed to simplify the setup, training, and visualization of Physics Information Neural Networks (PINNs). Built on DeepXDE, this tool allows users to directly define partial differential equations (PDEs), coupled multi-output systems, one-dimensional or two-dimensional domains, and boundary initial conditions, as well as configure network architectures and custom training plans. PINNStudio automatically generates local code, runs models, streams training logs, and displays loss curves and solutions in real time within the app; it also includes built-in templates for classic equations such as heat conduction, Allen-Cahn, and Cahn-Hilliard. This project was submitted by /u/Impossible-Jello2749. Thanks to Lu Lu and the DeepXDE team for laying the foundation; this tool is aimed at researchers and students with limited programming experience or those seeking efficient workflows.