Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems
☆109Apr 15, 2022Updated 3 years ago
Alternatives and similar repositories for gpinn
Users that are interested in gpinn are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆40Jul 12, 2023Updated 2 years ago
- Demo code for PPINN paper: https://www.sciencedirect.com/science/article/pii/S0045782520304357☆11Oct 23, 2020Updated 5 years ago
- Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonli…☆259Feb 1, 2023Updated 3 years ago
- Physics-informed neural networks with hard constraints for inverse design☆155Nov 21, 2021Updated 4 years ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆77Feb 1, 2023Updated 3 years ago
- End-to-end encrypted cloud storage - Proton Drive • AdSpecial offer: 40% Off Yearly / 80% Off First Month. Protect your most important files, photos, and documents from prying eyes.
- A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks☆105Oct 24, 2022Updated 3 years ago
- Reliable extrapolation of deep neural operators informed by physics or sparse observations☆29Jun 4, 2023Updated 2 years ago
- Use of Turbulence Model (Spalart-Allmaras) with PINNs for mean flow reconstruction☆13Mar 13, 2024Updated 2 years ago
- Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]☆286Oct 12, 2021Updated 4 years ago
- Python codes for Locally Adaptive Activation Function (LAAF) used in deep neural networks. Please cite this work as "A D Jagtap, K Kawa…☆44Feb 1, 2023Updated 3 years ago
- ☆253Oct 14, 2021Updated 4 years ago
- PINN in solving Navier–Stokes equation☆129Jun 7, 2020Updated 5 years ago
- Physics-informed neural network for solving fluid dynamics problems☆271Jan 28, 2021Updated 5 years ago
- PyTorch Implementation of Physics-informed Neural Networks☆708May 20, 2024Updated last year
- Virtual machines for every use case on DigitalOcean • AdGet dependable uptime with 99.99% SLA, simple security tools, and predictable monthly pricing with DigitalOcean's virtual machines, called Droplets.
- ☆211Feb 16, 2024Updated 2 years ago
- Must-read Papers on Physics-Informed Neural Networks.☆1,464Dec 8, 2023Updated 2 years ago
- ☆169Jun 27, 2022Updated 3 years ago
- Physics Informed Neural Networks (PINNs) is a machine learning technique that incorporates physical laws and constraints into the neural …☆12Sep 27, 2024Updated last year
- Code accompanying "Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks", Maddu et al., 2021☆14Nov 3, 2021Updated 4 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆89Aug 26, 2025Updated 7 months ago
- Deep Learning of Vortex Induced Vibrations☆99Feb 21, 2020Updated 6 years ago
- A pytorch implementation of several approaches using PINN to slove turbulent flow☆97Apr 4, 2024Updated 2 years ago
- Physics-informed neural networks package☆346Jul 20, 2022Updated 3 years ago
- Open source password manager - Proton Pass • AdSecurely store, share, and autofill your credentials with Proton Pass, the end-to-end encrypted password manager trusted by millions.
- [NeurIPS 2024] Codebase for PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs.☆413Feb 11, 2026Updated 2 months ago
- Accelerating Physics Informed Neural Networks (PINNs) using Meshless Discretizations☆34Apr 15, 2023Updated 2 years ago
- ☆16Jan 18, 2024Updated 2 years ago
- MIONet: Learning multiple-input operators via tensor product☆46Nov 13, 2022Updated 3 years ago
- Code accompanying the manuscript "Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition m…☆16Sep 18, 2023Updated 2 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆50Jul 23, 2020Updated 5 years ago
- A pytorch implementaion of physics informed neural networks for two dimensional NS equation☆194Apr 7, 2024Updated 2 years ago
- A library for scientific machine learning and physics-informed learning☆4,029Mar 1, 2026Updated last month
- PECANNs: Physics and Equality Constrained Artificial Neural Networks☆24Mar 30, 2026Updated last week
- Managed hosting for WordPress and PHP on Cloudways • AdManaged hosting with the flexibility to host WordPress, Magento, Laravel, or PHP apps, on multiple cloud providers. Cloudways by DigitalOcean.
- A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data☆369Jul 14, 2023Updated 2 years ago
- ☆26Jul 7, 2022Updated 3 years ago
- Physics Informed Neural Network (PINN) for the wave equation.☆205Jul 16, 2020Updated 5 years ago
- Investigating PINNs☆752Aug 13, 2021Updated 4 years ago
- Effective data sampling strategies and boundary condition constraints of physics-informed neural networks for identifying material proper…☆25Jul 3, 2023Updated 2 years ago
- Tutorials on deep learning, Python, and dissipative particle dynamics☆214Mar 21, 2026Updated 3 weeks ago
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆61Jan 25, 2022Updated 4 years ago