Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs
☆33Mar 19, 2026Updated 3 weeks ago
Alternatives and similar repositories for PhyCRNet
Users that are interested in PhyCRNet are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Physics-informed deep super-resolution of spatiotemporal data☆48Sep 5, 2023Updated 2 years ago
- This repo includes the dataset/code of 3D Convolutional Neural Network for material property prediction☆20Aug 15, 2020Updated 5 years ago
- Physics-encoded recurrent convolutional neural network☆48Jan 3, 2022Updated 4 years ago
- A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.☆27Sep 30, 2021Updated 4 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆169May 15, 2024Updated last year
- Managed Kubernetes at scale on DigitalOcean • AdDigitalOcean Kubernetes includes the control plane, bandwidth allowance, container registry, automatic updates, and more for free.
- physics-informed neural network for elastodynamics problem☆161Jan 20, 2022Updated 4 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
- ☆14Mar 3, 2022Updated 4 years ago
- Official code for AL-PINNS: Augmented Lagrangian relaxation method for Physics-Informed Neural Networks☆12Jul 29, 2023Updated 2 years ago
- Accelerating Physics Informed Neural Networks (PINNs) using Meshless Discretizations☆34Apr 15, 2023Updated 3 years ago
- ☆26Jul 10, 2025Updated 9 months ago
- PINN-COVID analyzes a plurality of epidemiological models through the lens of physics-informed neural networks (PINNs).☆22Oct 12, 2021Updated 4 years ago
- ☆13Apr 7, 2022Updated 4 years ago
- 2D Lid Driven Cavity Flow Simulations: FEM vs FDM vs SIMPLE☆15Jun 2, 2019Updated 6 years ago
- Managed Kubernetes at scale on DigitalOcean • AdDigitalOcean Kubernetes includes the control plane, bandwidth allowance, container registry, automatic updates, and more for free.
- Generative Pre-Trained Physics-Informed Neural Networks Implementation☆120Aug 26, 2025Updated 7 months ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆78Feb 1, 2023Updated 3 years ago
- Discontinuity Computing Using Physics-Informed Neural Network☆29Apr 20, 2024Updated last year
- 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
- Project under CSF407 - AI☆13Jun 24, 2024Updated last year
- PECANNs: Physics and Equality Constrained Artificial Neural Networks☆25Mar 30, 2026Updated 2 weeks ago
- Physics-informed neural network for solving fluid dynamics problems☆271Jan 28, 2021Updated 5 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆90Aug 26, 2025Updated 7 months ago
- Managed hosting for WordPress and PHP on Cloudways • AdManaged hosting for WordPress, Magento, Laravel, or PHP apps, on multiple cloud providers. Deploy in minutes on Cloudways by DigitalOcean.
- Code for reproducing the paper: RANG: A Residual-based Adaptive Node Generation Method for Physics-Informed Neural Networks☆16May 2, 2022Updated 3 years ago
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆61Jan 25, 2022Updated 4 years ago
- Physics-Informed deep LSTM architecture to forecast Lorenz and MFE fluid systems☆14May 18, 2020Updated 5 years ago
- Physcial Informed Extreme Learning Machine(PIELM) method to solve PDEs, such as Possion problem☆19Dec 6, 2024Updated last year
- Deep Learning based method to try and learn the problem of inverse Navier Stokes and model the flow for an oscillating airfoil.☆24Jun 7, 2020Updated 5 years ago
- Physics Informed Neural Network (PINN) for the 2D Navier-Stokes equation☆41Jun 24, 2022Updated 3 years ago
- Using deep reinforcement learning for refining meshes in computational fluid dynamics☆30Aug 7, 2023Updated 2 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
- Adaptive Swarm Mesh Refinement☆21Apr 8, 2024Updated 2 years ago
- AI Agents on DigitalOcean Gradient AI Platform • AdBuild production-ready AI agents using customizable tools or access multiple LLMs through a single endpoint. Create custom knowledge bases or connect external data.
- Finite Volume PINNs for Hyperbolic Conservation Laws & Compressible Flow☆24Nov 29, 2022Updated 3 years ago
- Flow field reconstruction and prediction of the 2D cylinder flow using data-driven physics-informed neural network combined with long sho…☆42Nov 11, 2024Updated last year
- A Self-Training Physics-Informed Neural Network for Partial Differential Equations☆23Aug 3, 2023Updated 2 years ago
- Encoding physics to learn reaction-diffusion processes☆110Aug 28, 2023Updated 2 years ago
- Enhancing the convergence speed by 2x and improving the training success of Physics-Informed Neural Networks (PINNs).☆13Oct 14, 2024Updated last year
- Codebase for Master's dissertation in Mathematics at Durham University. Topic: applying neural networks to differential equations. Grade:…☆17Aug 17, 2023Updated 2 years ago
- ☆15Mar 6, 2024Updated 2 years ago