thuml / Transolver
About code release of "Transolver: A Fast Transformer Solver for PDEs on General Geometries", ICML 2024 Spotlight. https://arxiv.org/abs/2402.02366
☆135Updated last month
Alternatives and similar repositories for Transolver:
Users that are interested in Transolver are comparing it to the libraries listed below
- ☆71Updated 6 months ago
- About Code Release for "Solving High-Dimensional PDEs with Latent Spectral Models" (ICML 2023), https://arxiv.org/abs/2301.12664☆68Updated 11 months ago
- ☆115Updated 5 months ago
- ☆68Updated last year
- ICON for in-context operator learning☆46Updated last month
- Geometry-Aware Fourier Neural Operator (Geo-FNO)☆218Updated last year
- A large-scale benchmark for machine learning methods in fluid dynamics☆166Updated 3 months ago
- Code for "DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training"☆52Updated 9 months ago
- DeepONet & FNO (with practical extensions)☆272Updated last year
- Code for "DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training"☆44Updated 9 months ago
- Code for the paper "Poseidon: Efficient Foundation Models for PDEs"☆138Updated 3 months ago
- ☆27Updated last month
- Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey☆150Updated last month
- [NeurIPS 2022] Minimizing L_inf Physics-Informed Loss for PINN with adversarial training☆38Updated 2 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆146Updated 10 months ago
- Source code for Separable PINN☆66Updated last year
- [ICLR24] A boundary-embedded neural operator that incorporates complex boundary shape and inhomogeneous boundary values☆25Updated 3 months ago
- ☆38Updated last year
- ☆157Updated last year
- Benchmarking Autoregressive Conditional Diffusion Models for Turbulent Flow Simulation☆82Updated 3 months ago
- Repo to the paper "Message Passing Neural PDE Solvers"☆131Updated 6 months ago
- Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."☆57Updated 7 months ago
- ☆47Updated 2 months ago
- ☆27Updated 8 months ago
- Characterizing possible failure modes in physics-informed neural networks.☆128Updated 3 years ago
- This repository is the official implementation of the paper Convolutional Neural Operators for robust and accurate learning of PDEs☆156Updated 5 months ago
- Encoding physics to learn reaction-diffusion processes☆94Updated last year
- ☆44Updated 3 months ago
- Non-adaptive and residual-based adaptive sampling for PINNs☆65Updated 2 years ago
- ☆106Updated last month