Code accompanying my blog post: So, what is a physics-informed neural network?
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Updated
Mar 22, 2022 - Jupyter Notebook
Code accompanying my blog post: So, what is a physics-informed neural network?
PyTorch Implementation of Physics-informed Neural Networks
Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs)
Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]
PINNs-Torch, Physics-informed Neural Networks (PINNs) implemented in PyTorch.
Using Physics-Informed Deep Learning (PIDL) techniques (W-PINNs-DE & W-PINNs) to solve forward and inverse hydrodynamic shock-tube problems and plane stress linear elasticity boundary value problems
Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed computing
PINNs-TF2, Physics-informed Neural Networks (PINNs) implemented in TensorFlow V2.
Efficient, Accurate, and Streamlined Training of Physics-Informed Neural Networks
Public repository for the proposal “Physics-Informed Machine Learning Simulator for Wildfire Propagation” - MLJC University of Turin - ProjectX2020 Competition (UofT AI)
Using NVIDIA modulus for airfoil optimizations at different angles.
resources pour le cours d'introduction à la programmation des GPUs du mastère spécialisé HPC-AI
PINNs-JAX, Physics-informed Neural Networks (PINNs) implemented in JAX.
Yet another PINN implementation
Physics-Informed Neural Networks Trained with Particle Swarm Optimization
Official implementation of Conflict-Free Inverse Gradients Method
Replication with PyTorch of ''Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations'' by M. Raissi, P. Perdikaris, and G.E. Karniadakis from 2019.
Physics-informed neural networks (PINNs)
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