Physics-informed neural networks with hard constraints for inverse design
☆166Nov 21, 2021Updated 4 years ago
Alternatives and similar repositories for hpinn
Users that are interested in hpinn are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems☆115Apr 15, 2022Updated 4 years ago
- ☆13Dec 15, 2021Updated 4 years ago
- ☆178Jun 27, 2022Updated 4 years ago
- A library for scientific machine learning and physics-informed learning☆4,497Updated this week
- ☆63Jul 24, 2019Updated 7 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.
- Code accompanying the manuscript "Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition m…☆16Sep 18, 2023Updated 3 years ago
- A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks☆108Oct 24, 2022Updated 4 years ago
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆62Jan 25, 2022Updated 4 years ago
- Tutorials on deep learning, Python, and dissipative particle dynamics☆230Mar 21, 2026Updated 7 months ago
- This is the source code for our paper "Towards high-accuracy deep learning inference of compressible turbulent flows over aerofoils"☆34Mar 11, 2024Updated 2 years ago
- MIONet: Learning multiple-input operators via tensor product☆47Nov 13, 2022Updated 3 years ago
- ☆433Dec 3, 2022Updated 3 years ago
- Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators☆857Jun 25, 2022Updated 4 years ago
- A hybrid Decoder-DeepONet operator regression framework for unaligned observation data☆10Jul 16, 2023Updated 3 years ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]☆300Oct 12, 2021Updated 5 years ago
- Super-resolution and denoising of fluid flow using physics-informed convolutional neural networks without high-resolution labels -- param…☆25Aug 2, 2021Updated 5 years ago
- ☆13Nov 20, 2019Updated 6 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆49Jul 23, 2020Updated 6 years ago
- A simple Linux command-line utility which submits a job to one of the multiple GPU servers☆12Aug 16, 2024Updated 2 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆91Jan 24, 2021Updated 5 years ago
- Ensembe PINN for improved inverse modeling☆11Apr 26, 2023Updated 3 years ago
- ☆17Jun 7, 2025Updated last year
- 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
- Managed Kubernetes at scale on DigitalOcean • AdDigitalOcean Kubernetes includes the control plane, bandwidth allowance, container registry, automatic updates, and more for free.
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆44Jul 12, 2023Updated 3 years ago
- Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data☆155Oct 18, 2019Updated 7 years ago
- Must-read Papers on Physics-Informed Neural Networks.☆1,558Dec 8, 2023Updated 2 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆96Aug 26, 2025Updated last year
- Enhancing the convergence speed by 2x and improving the training success of Physics-Informed Neural Networks (PINNs).☆14Oct 14, 2024Updated 2 years ago
- ☆57Oct 9, 2022Updated 4 years ago
- ☆274Oct 14, 2021Updated 5 years ago
- Optical bench simulation code for analyzing the Fresnel Incoherent Holography (FINCH) setup.☆10Jun 2, 2022Updated 4 years ago
- Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations☆6,242Feb 11, 2026Updated 8 months ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- ☆79Nov 15, 2022Updated 3 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
- Physics-guided neural network framework for elastic plates☆51Mar 24, 2022Updated 4 years ago
- Original implementation of fast PINN optimization with RBA weights☆79Sep 11, 2025Updated last year
- Physics-informed neural network for solving fluid dynamics problems☆294Jan 28, 2021Updated 5 years ago
- ☆38Feb 13, 2022Updated 4 years ago
- A place to share problems solved with SciANN☆311Nov 6, 2023Updated 3 years ago