Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs
☆34Mar 19, 2026Updated 4 months 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☆50Sep 5, 2023Updated 2 years ago
- This repo includes the dataset/code of 3D Convolutional Neural Network for material property prediction☆20Aug 15, 2020Updated 6 years ago
- Physics-encoded recurrent convolutional neural network☆49Jan 3, 2022Updated 4 years ago
- A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.☆28Sep 30, 2021Updated 4 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆169May 15, 2024Updated 2 years ago
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- physics-informed neural network for elastodynamics problem☆163Jan 20, 2022Updated 4 years ago
- Project under CSF407 - AI☆13Jun 24, 2024Updated 2 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
- Enhancing the convergence speed by 2x and improving the training success of Physics-Informed Neural Networks (PINNs).☆13Oct 14, 2024Updated last year
- Official code for AL-PINNS: Augmented Lagrangian relaxation method for Physics-Informed Neural Networks☆12Jul 29, 2023Updated 3 years ago
- Accelerating Physics Informed Neural Networks (PINNs) using Meshless Discretizations☆36Apr 15, 2023Updated 3 years ago
- ☆26Jul 10, 2025Updated last year
- ☆13Apr 7, 2022Updated 4 years ago
- PINN-COVID analyzes a plurality of epidemiological models through the lens of physics-informed neural networks (PINNs).☆22Oct 12, 2021Updated 4 years ago
- Deploy to Railway using AI coding agents - Free Credits Offer • AdUse Claude Code, Codex, OpenCode, and more. Autonomous software development now has the infrastructure to match with Railway.
- Generative Pre-Trained Physics-Informed Neural Networks Implementation☆122Aug 26, 2025Updated 11 months ago
- 2D Lid Driven Cavity Flow Simulations: FEM vs FDM vs SIMPLE☆14Jun 2, 2019Updated 7 years ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆82Feb 1, 2023Updated 3 years ago
- Discontinuity Computing Using Physics-Informed Neural Network☆29Apr 20, 2024Updated 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…☆271Feb 1, 2023Updated 3 years ago
- PECANNs: Physics and Equality Constrained Artificial Neural Networks☆26Mar 30, 2026Updated 4 months ago
- Physics-informed neural network for solving fluid dynamics problems☆284Jan 28, 2021Updated 5 years ago
- ☆15Mar 3, 2022Updated 4 years 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.
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆63Jan 25, 2022Updated 4 years ago
- Code for reproducing the paper: RANG: A Residual-based Adaptive Node Generation Method for Physics-Informed Neural Networks☆16May 2, 2022Updated 4 years ago
- Physics-Informed deep LSTM architecture to forecast Lorenz and MFE fluid systems☆14May 18, 2020Updated 6 years ago
- 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 6 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆95Aug 26, 2025Updated 11 months 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☆22Apr 8, 2024Updated 2 years ago
- Using deep reinforcement learning for refining meshes in computational fluid dynamics☆32Aug 7, 2023Updated 3 years ago
- Physics-Informed Neural Networks Trained with Particle Swarm Optimization☆29Sep 20, 2022Updated 3 years ago
- Managed Kubernetes at scale on DigitalOcean • AdDigitalOcean Kubernetes includes the control plane, bandwidth allowance, container registry, automatic updates, and more for free.
- A Self-Training Physics-Informed Neural Network for Partial Differential Equations☆25Aug 3, 2023Updated 3 years ago
- Official repository for the "Multiple wavefield solutions in physics-informed neural networks using latent representation" paper.☆15May 1, 2025Updated last year
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆92Jan 24, 2021Updated 5 years ago
- Encoding physics to learn reaction-diffusion processes☆111Aug 28, 2023Updated 2 years ago
- A simple Physics Informed Neural Network (PINN) implementation in TensorFlow 2 for magnetic field mapping using finite amount of magnetic…☆14Jun 7, 2022Updated 4 years ago
- Bayesian autoencoders for data-driven discovery of coordinates, governing equations and fundamental constants. Proceedings of the Royal S…☆11Jul 9, 2024Updated 2 years ago
- code accompanying the 2018 Soft Matter paper "Mechanics of biomimetic 4D printed structures"☆13Jul 2, 2025Updated last year