Physics-Informed Neural Networks: Forward/Inverse Modeling of Partial Differential Equations
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Jun 10, 2026 - Python
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deepxde
Here are 11 public repositories matching this topic...
Physics-informed neural networks (PINNs) for forward simulation and inverse parameter estimation in 2D martensitic phase transformations.
pytorch inverse-problems phase-field scientific-machine-learning physics-informed-learning computational-materials-science physics-informed-neural-networks deepxde materials-science-simulations phase-field-modeling martensitic-transformation
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Apr 28, 2026 - Python
No-code GUI for Physics-Informed Neural Networks (PINNs)
deep-learning pytorch computational-sciences pinn pde-solver scientific-machine-learning pyqt6 physics-informed-neural-networks deepxde
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Sep 1, 2026 - Python
A library of XDE cases and algorithm
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Jul 25, 2024 - Python
🧮 PINN Enterprise Platform - AI-Powered Physics Simulations with CopilotKit-style Research Canvas UI. Complete serverless architecture with RAG-powered code generation, 3D visualization, and global edge deployment.
webgl machine-learning serverless scientific-computing heat-transfer physics-simulation fluid-dynamics 3d-visualization engineering-simulation pinn cloudflare-workers fastapi physics-informed-neural-networks deepxde enterprise-platform ai-simulation copilotkit rag-system research-canvas
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Jul 13, 2025 - Python
Making an ML PINN model for the ML4EO hackathon
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Feb 2, 2024 - Python
Solving Torrey-Bloch Equations via Physics-Informed Neural Networks (PINNs)
deep-learning partial-differential-equations diffusion pinns physics-informed-neural-networks deepxde
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Jun 7, 2022 - Jupyter Notebook
(Surrogate Cantilever)A PINN model built with DeepXDE and PyTorch to solve the Euler-Bernoulli cantilever beam equation. Features analytical solution comparisons and an interactive frontend visualization.
visualization machine-learning pytorch scientific-computing pinn physics-informed-neural-networks deepxde cantilever-beam euler-bernoulli
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May 13, 2026 - Python
Solving 1D beam, 2D plate, and 3D solid mechanics problems using Physics-Informed Neural Networks (PINNs) with DeepXDE and TensorFlow. Results validated against ANSYS Mechanical 2025 R1. 2nd sem project
tensorflow solid-mechanics ansys-fluent navier-stokes-equations kirchhoff-thin-plate scientific-ml pinns deepxde euler-bernoulli
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Apr 28, 2026 - Python
This project implements a Physics-Informed Neural Network (PINN) using DeepXDE to approximate the gravitational potential field of a two-body system (e.g., Earth and Moon). By embedding Newtonian physics laws into the loss function, the model learns to satisfy both data-driven and physical constraints, demonstrating the fusion of AI and physics.
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Nov 9, 2025 - Jupyter Notebook
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