a1k12 / characterizing-pinns-failure-modes
Characterizing possible failure modes in physics-informed neural networks.
☆122Updated 3 years ago
Related projects ⓘ
Alternatives and complementary repositories for characterizing-pinns-failure-modes
- ☆146Updated 9 months ago
- ☆115Updated 2 years ago
- ☆174Updated 3 years ago
- ☆152Updated 8 months ago
- ☆85Updated 3 years ago
- ☆280Updated last year
- Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]☆180Updated 3 years ago
- ☆52Updated 2 years ago
- DeepONet & FNO (with practical extensions)☆223Updated last year
- This repository is the official implementation of the paper Convolutional Neural Operators for robust and accurate learning of PDEs☆133Updated last month
- Applications of PINOs☆109Updated 2 years ago
- Geometry-Aware Fourier Neural Operator (Geo-FNO)☆183Updated last year
- ☆83Updated last month
- Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonli…☆154Updated last year
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆124Updated 6 months ago
- Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data☆138Updated 5 years ago
- Non-adaptive and residual-based adaptive sampling for PINNs☆58Updated 2 years ago
- ☆368Updated 8 months ago
- Codebase for PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs.☆247Updated 3 months ago
- PINN (Physics-Informed Neural Networks) on Navier-Stokes Equations☆76Updated 2 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆61Updated last year
- hPINN: Physics-informed neural networks with hard constraints☆115Updated 3 years ago
- Physics informed neural network (PINN) for cavity flow governed by Navier-Stokes equation.☆125Updated 4 years ago
- ☆229Updated last week
- Code for the paper "Poseidon: Efficient Foundation Models for PDEs"☆104Updated last month
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆82Updated 3 years ago
- Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs…☆315Updated 5 months ago
- ☆94Updated 4 months ago
- ☆50Updated 2 years ago