823 skills found · Page 1 of 28
maziarraissi / PINNsPhysics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations
lululxvi / DeepxdeA library for scientific machine learning and physics-informed learning
SciML / ModelingToolkit.jlAn acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations
idrl-lab / PINNpapersMust-read Papers on Physics-Informed Neural Networks.
pnnl / NeuromancerPytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.
SciML / NeuralPDE.jlPhysics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
SciML / DiffEqFlux.jlPre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods
rezaakb / Pinns TorchPINNs-Torch, Physics-informed Neural Networks (PINNs) implemented in PyTorch.
prateekbhustali / Physics Informed Neural NetworksInvestigating PINNs
mathLab / PINAPhysics-Informed Neural networks for Advanced modeling
jayroxis / PINNsPyTorch Implementation of Physics-informed Neural Networks
benmoseley / Harmonic Oscillator PinnCode accompanying my blog post: So, what is a physics-informed neural network?
jdtoscano94 / NABLA SciMLPhysics Informed Machine Learning Tutorials (Pytorch and Jax)
benmoseley / FBPINNsSolve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs)
neuraloperator / Physics InformedNo description available
wang-fujin / PINN4SOHA physics-informed neural network for battery SOH estimation
i207M / PINNacle[NeurIPS 2024] Codebase for PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs.
PredictiveIntelligenceLab / Physics Informed DeepONetsNo description available
peterdsharpe / NeuralFoilNeuralFoil is a practical airfoil aerodynamics analysis tool using physics-informed machine learning, exposed to end-users in pure Python/NumPy.
Jianghanxiao / PhysTwin[ICCV 2025] PhysTwin: Physics-Informed Reconstruction and Simulation of Deformable Objects from Videos
