A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks
☆106Oct 24, 2022Updated 3 years ago
Alternatives and similar repositories for pinn-sampling
Users that are interested in pinn-sampling are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Reliable extrapolation of deep neural operators informed by physics or sparse observations☆29Jun 4, 2023Updated 2 years ago
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆29May 8, 2023Updated 2 years ago
- Official code for "DMIS: Dynamic Mesh-based Importance Sampling for Training Physics-Informed Neural Networks" (AAAI 2023)☆18Jan 17, 2024Updated 2 years ago
- Physics-informed neural networks with hard constraints for inverse design☆156Nov 21, 2021Updated 4 years ago
- Original implementation of fast PINN optimization with RBA weights☆73Sep 11, 2025Updated 7 months ago
- Deploy open-source AI quickly and easily - Special Bonus Offer • AdRunpod Hub is built for open source. One-click deployment and autoscaling endpoints without provisioning your own infrastructure.
- Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems☆109Apr 15, 2022Updated 4 years ago
- Physics-informed neural networks (PINNs)☆16Jun 7, 2022Updated 3 years ago
- ☆73Nov 15, 2022Updated 3 years ago
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆39Jul 12, 2023Updated 2 years ago
- ☆172Jun 27, 2022Updated 3 years ago
- ☆18Jun 6, 2023Updated 2 years ago
- ☆215Feb 16, 2024Updated 2 years ago
- Solving a class of elliptic partial differential equations(PDEs) with multiple scales utilizing Fourier-based mixed physics informed neur…☆15Apr 12, 2024Updated 2 years ago
- ☆12Apr 18, 2023Updated 3 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.
- Official code for DPM : A Novel Training Method for Physics-Informed Neural Networks in Extrapolation☆10Nov 2, 2021Updated 4 years ago
- Fourier-MIONet: Fourier-enhanced multiple-input neural operators for multiphase modeling of geological carbon sequestration☆19Sep 7, 2024Updated last year
- code☆20Sep 8, 2023Updated 2 years ago
- ☆35Jan 10, 2025Updated last year
- TensorFlow 2.0 implementation of Maziar Raissi's Physics Informed Neural Networks (PINNs).☆267Nov 30, 2023Updated 2 years ago
- DAS: A deep adaptive sampling method for solving high-dimensional partial differential equations☆40Nov 20, 2024Updated last year
- A library for scientific machine learning and physics-informed learning☆4,123Mar 1, 2026Updated 2 months ago
- [NeurIPS 2024] Codebase for PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs.☆418Feb 11, 2026Updated 2 months ago
- DiffNet: A FEM based neural PDE solver package☆12Apr 9, 2024Updated 2 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.
- Optimizing Physics-Informed NN using Multi-task Likelihood Loss Balance Algorithm and Adaptive Activation Function Algorithm☆34Jun 2, 2023Updated 2 years ago
- ☆16Dec 13, 2022Updated 3 years ago
- SeismicNet: Physics-informed neural networks for seismic wave modeling in semi-infinite domain☆19May 5, 2024Updated 2 years ago
- ☆17Nov 26, 2024Updated 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
- Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs…☆540Mar 26, 2026Updated last month
- ☆258Oct 14, 2021Updated 4 years ago
- ☆12Aug 22, 2025Updated 8 months ago
- Physics Informed Neural Networks: a starting step for CFD specialists☆41May 12, 2022Updated 3 years ago
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- Physics-informed learning of governing equations from scarce data☆170Jul 19, 2023Updated 2 years ago
- Demo code for PPINN paper: https://www.sciencedirect.com/science/article/pii/S0045782520304357☆11Oct 23, 2020Updated 5 years ago
- Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]☆293Oct 12, 2021Updated 4 years ago
- Code accompanying "Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks", Maddu et al., 2021☆14Nov 3, 2021Updated 4 years ago
- ☆26Jul 7, 2022Updated 3 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
- XPINN code written in TensorFlow 2☆28Feb 1, 2023Updated 3 years ago