☆551Apr 1, 2025Updated last year
Alternatives and similar repositories for physics_informed
Users that are interested in physics_informed are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Applications of PINOs☆150Oct 10, 2022Updated 3 years ago
- Learning in infinite dimension with neural operators.☆3,894Aug 6, 2026Updated last month
- Geometry-Aware Fourier Neural Operator (Geo-FNO)☆353Apr 16, 2026Updated 5 months ago
- ☆428Dec 3, 2022Updated 3 years ago
- A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data☆395Jul 14, 2023Updated 3 years ago
- GPUs on demand by Runpod - Special Offer Available • AdRun AI, ML, and HPC workloads on powerful cloud GPUs—without limits or wasted spend. Deploy GPUs in under a minute and pay by the second.
- PDEBench: An Extensive Benchmark for Scientific Machine Learning☆1,201Mar 30, 2026Updated 5 months ago
- ☆1,124Updated this week
- Using graph network to solve PDEs☆453Jun 2, 2025Updated last year
- A library for scientific machine learning and physics-informed learning☆4,429Aug 18, 2026Updated last month
- DeepONets, (Fourier) Neural Operators, Physics-Informed Neural Operators, and more in Julia☆292Sep 28, 2024Updated last year
- [ICLR 2023] Factorized Fourier Neural Operators☆199Oct 13, 2023Updated 2 years ago
- This repository is the official implementation of the paper Convolutional Neural Operators for robust and accurate learning of PDEs☆231Nov 24, 2025Updated 9 months ago
- Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators☆845Jun 25, 2022Updated 4 years ago
- ☆313Sep 14, 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.
- U-FNO - an enhanced Fourier neural operator-based deep-learning model for multiphase flow☆178Sep 6, 2024Updated 2 years ago
- ☆57Oct 9, 2022Updated 3 years ago
- This repository contains the code for the paper: Deciphering and integrating invariants for neural operator learning with various physica…☆13Mar 18, 2024Updated 2 years ago
- ☆16Nov 20, 2023Updated 2 years ago
- Adaptive FNO transformer - official Pytorch implementation☆289Nov 7, 2022Updated 3 years ago
- ☆68Mar 21, 2025Updated last year
- A library for Koopman Neural Operator with Pytorch.☆332Oct 5, 2024Updated last year
- Code for "DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training"☆74Jun 10, 2024Updated 2 years ago
- Characterizing possible failure modes in physics-informed neural networks.☆152Nov 18, 2021Updated 4 years ago
- Managed Database hosting by DigitalOcean • AdPostgreSQL, MySQL, MongoDB, Kafka, Valkey, and OpenSearch available. Automatically scale up storage and focus on building your apps.
- ☆95Jul 18, 2023Updated 3 years ago
- Here you find the Spectral Operator Learning Under construcTION☆21May 8, 2024Updated 2 years ago
- [ICLR 2024] Scaling physics-informed hard constraints with mixture-of-experts.☆42Jun 21, 2024Updated 2 years ago
- ☆16Oct 25, 2021Updated 4 years ago
- [NeurIPS 2021] Galerkin Transformer: Neural Operator built on Attention for PDEs☆268Jun 14, 2024Updated 2 years ago
- Repo to the paper "Message Passing Neural PDE Solvers"☆151Sep 11, 2024Updated 2 years ago
- Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]☆299Oct 12, 2021Updated 4 years ago
- ☆49Jul 6, 2023Updated 3 years ago
- ☆49Dec 7, 2022Updated 3 years ago
- GPU virtual machines on DigitalOcean Gradient AI • AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- Must-read Papers on Physics-Informed Neural Networks.☆1,543Dec 8, 2023Updated 2 years ago
- Code for "DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training"☆61Jun 10, 2024Updated 2 years ago
- This is the implementation of the RecFNO.☆27Feb 21, 2023Updated 3 years ago
- Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs…☆577May 29, 2026Updated 3 months ago
- Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations☆6,154Feb 11, 2026Updated 7 months ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆169May 15, 2024Updated 2 years ago
- Physics Informed Fourier Neural Operator☆32Nov 21, 2024Updated last year