[TMLR] CodePDE: An Inference Framework for LLM-driven PDE Solver Generation
☆82Feb 12, 2026Updated 5 months ago
Alternatives and similar repositories for CodePDE
Users that are interested in CodePDE are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- ☆29Jun 12, 2025Updated last year
- ☆26May 21, 2024Updated 2 years ago
- PDEAgentBench: An automated benchmark framework for evaluating Code Agents on optimizing scientific PDE solvers.☆41Jul 13, 2026Updated last week
- ☆18Aug 17, 2024Updated last year
- Official implementation of Scalable Transformer for PDE surrogate modelling☆57Mar 23, 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.
- ☆11Jan 7, 2025Updated last year
- ☆39Jul 9, 2025Updated last year
- Code for the paper "Poseidon: Efficient Foundation Models for PDEs"☆190Apr 10, 2025Updated last year
- PROSE: Predicting Multiple Operators and Symbolic Expressions☆37Nov 10, 2025Updated 8 months ago
- ☆310Sep 14, 2024Updated last year
- Code for "DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training"☆57Jun 10, 2024Updated 2 years ago
- Latent Mamba Operator for Partial Differential Equations☆17Jun 3, 2025Updated last year
- [ICLR 2025] Neural Operator-Assisted Computational Fluid Dynamics in PyTorch☆82Nov 21, 2025Updated 7 months ago
- ☆96Sep 2, 2024Updated last year
- AI Agents on DigitalOcean Gradient AI Platform • AdBuild production-ready AI agents using customizable tools or access multiple LLMs through a single endpoint. Create custom knowledge bases or connect external data.
- This repository contains code for the paper "MAgNet: Mesh-Agnostic Neural PDE Solver" https://arxiv.org/abs/2210.05495☆39Jun 21, 2023Updated 3 years ago
- A curated paper list for "Foundation Neural Operators: A Survey on Pretraining Methods, Data Ecosystems, and Efficient Adaptation".☆36Feb 14, 2026Updated 5 months ago
- Inducing Point Operator Transformer: A Flexible and Scalable Architecture for Solving PDEs (AAAI 2024)☆14Jul 30, 2024Updated last year
- One-shot learning for solution operators of partial differential equations☆30Nov 20, 2025Updated 8 months ago
- ☆24Mar 3, 2023Updated 3 years ago
- ☆62Jun 18, 2026Updated last month
- Benchmarking of diffusion models for global field reconstruction from sparse observations☆33Mar 22, 2026Updated 3 months ago
- ☆18Aug 13, 2024Updated last year
- PDE-Transformer is a neural network architecture designed to efficiently process and predict the evolution of physical systems described …☆87Apr 11, 2026Updated 3 months 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.
- ☆26Sep 1, 2025Updated 10 months ago
- [ICML 2024] Official PyTorch implementation of the Vectorized Conditional Neural Field.☆18Aug 1, 2024Updated last year
- [ICLR24] A boundary-embedded neural operator that incorporates complex boundary shape and inhomogeneous boundary values☆33Dec 5, 2024Updated last year
- ☆13Mar 21, 2024Updated 2 years ago
- PDEBench: An Extensive Benchmark for Scientific Machine Learning☆1,173Mar 30, 2026Updated 3 months ago
- Code for "DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training"☆72Jun 10, 2024Updated 2 years ago
- MIONet: Learning multiple-input operators via tensor product☆47Nov 13, 2022Updated 3 years ago
- Solving Inverse Physics Problems with Score Matching☆34Dec 4, 2023Updated 2 years ago
- Repository of GridMix (ICLR 2025)☆36Mar 18, 2025Updated last year
- Virtual machines for every use case on DigitalOcean • AdGet dependable uptime with 99.99% SLA, simple security tools, and predictable monthly pricing with DigitalOcean's virtual machines, called Droplets.
- ICON for in-context operator learning☆67May 3, 2026Updated 2 months ago
- Staggered HARd-constrained Physics-Informed Neural Networks for Phase-field modelling of corrosion☆16Feb 19, 2025Updated last year
- Official repository for "ProPINN: Demystifying Propagation Failures in Physics-Informed Neural Networks", https://arxiv.org/abs/2502.0080…☆16Oct 17, 2025Updated 9 months ago
- Quantum DeepONet: Neural operators accelerated by quantum computing☆22Jun 10, 2025Updated last year
- [ICML 2024] LLM and Simulation as Bilevel Optimizers: A New Paradigm to Advance Physical Scientific Discovery☆85May 31, 2024Updated 2 years ago
- ☆14Jan 22, 2022Updated 4 years ago
- [ICLR26] AI-based scaling law discovery☆31Jan 30, 2026Updated 5 months ago