Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
☆853Jun 25, 2022Updated 4 years ago
Alternatives and similar repositories for deeponet
Users that are interested in deeponet are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- ☆431Dec 3, 2022Updated 3 years ago
- A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data☆398Jul 14, 2023Updated 3 years ago
- A library for scientific machine learning and physics-informed learning☆4,467Aug 18, 2026Updated last month
- Learning in infinite dimension with neural operators.☆3,952Aug 6, 2026Updated 2 months ago
- ☆555Apr 1, 2025Updated last year
- 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.
- Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations☆6,203Feb 11, 2026Updated 8 months ago
- Geometry-Aware Fourier Neural Operator (Geo-FNO)☆357Apr 16, 2026Updated 5 months ago
- 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
- Tutorials on deep learning, Python, and dissipative particle dynamics☆229Mar 21, 2026Updated 6 months ago
- ☆1,125Sep 13, 2026Updated last month
- Physics Informed Machine Learning Tutorials (Pytorch and Jax)☆687Sep 12, 2026Updated last month
- ☆57Oct 9, 2022Updated 4 years ago
- MIONet: Learning multiple-input operators via tensor product☆47Nov 13, 2022Updated 3 years ago
- ☆178Jun 27, 2022Updated 4 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.
- ☆274Oct 14, 2021Updated 5 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆85Aug 4, 2023Updated 3 years ago
- A place to share problems solved with SciANN☆311Nov 6, 2023Updated 2 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
- ☆27Jul 7, 2022Updated 4 years ago
- Using graph network to solve PDEs☆453Jun 2, 2025Updated last year
- PyTorch Implementation of Physics-informed Neural Networks☆724May 20, 2024Updated 2 years ago
- ☆119Oct 16, 2021Updated 4 years ago
- [ICLR 2023] Factorized Fourier Neural Operators☆199Oct 13, 2023Updated 3 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.
- Implementing a physics-informed DeepONet from scratch☆64Jul 9, 2023Updated 3 years ago
- Implementation of the deep operator network in pytorch, with examples of solving Differential Equations☆17Mar 30, 2024Updated 2 years ago
- Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]☆301Oct 12, 2021Updated 5 years ago
- Physics-informed neural networks with hard constraints for inverse design☆165Nov 21, 2021Updated 4 years ago
- Must-read Papers on Physics-Informed Neural Networks.☆1,551Dec 8, 2023Updated 2 years ago
- A large-scale benchmark for machine learning methods in fluid dynamics☆303Oct 25, 2025Updated 11 months ago
- Physics-informed learning of governing equations from scarce data☆170Jul 19, 2023Updated 3 years ago
- PDEBench: An Extensive Benchmark for Scientific Machine Learning☆1,214Mar 30, 2026Updated 6 months ago
- Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems☆115Apr 15, 2022Updated 4 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.
- ☆129Jul 20, 2022Updated 4 years ago
- ☆50Jul 6, 2023Updated 3 years ago
- Characterizing possible failure modes in physics-informed neural networks.☆152Nov 18, 2021Updated 4 years ago
- Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."☆87Apr 24, 2025Updated last year
- ☆16Oct 25, 2021Updated 4 years ago
- Neural operator surrogates for electromagnetic inverse design☆52Feb 28, 2024Updated 2 years ago
- PDE-Net: Learning PDEs from Data☆332Jun 26, 2021Updated 5 years ago