BenediktAlkin / upt-tutorialLinks
Resources for UPT tutorials
☆14Updated 8 months ago
Alternatives and similar repositories for upt-tutorial
Users that are interested in upt-tutorial are comparing it to the libraries listed below
Sorting:
- ☆87Updated last year
- PyTorch implemention of the Position-induced Transformer for operator learning in partial differential equations☆25Updated 6 months ago
- Code for the paper Universal Physics Transformers☆146Updated 5 months ago
- Repo to the paper "Message Passing Neural PDE Solvers"☆140Updated last year
- Codomain attention neural operator for single to multi-physics PDE adaptation.☆70Updated 6 months ago
- Official implementation of Scalable Transformer for PDE surrogate modelling☆53Updated last year
- ☆47Updated 9 months ago
- Spectral Neural Operator☆78Updated last year
- Code for "DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training"☆54Updated last year
- ☆37Updated last year
- Code for "DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training"☆66Updated last year
- ☆85Updated 2 years ago
- [Neurips 2024] A benchmark suite for autoregressive neural emulation of PDEs. (≥46 PDEs in 1D, 2D, 3D; Differentiable Physics; Unrolled T…☆90Updated last month
- ☆56Updated 2 years ago
- This repository is the official implementation of the paper Convolutional Neural Operators for robust and accurate learning of PDEs☆198Updated 3 weeks ago
- Geometric Neural Operators (GNPs) for machine learning tasks on point-cloud representations: curvature estimation, shape deformations, so…☆31Updated last week
- [NeurIPS 2025] Geometry Aware Operator Transformer As An Efficient And Accurate Neural Surrogate For PDEs On Arbitrary Domains☆67Updated last month
- Benchmarking Autoregressive Conditional Diffusion Models for Turbulent Flow Simulation☆100Updated last year
- Code for Characterizing Scaling and Transfer Learning Behavior of FNO in SciML☆49Updated 2 years ago
- ☆54Updated 4 months ago
- Code for the paper "Poseidon: Efficient Foundation Models for PDEs"☆162Updated 8 months ago
- ☆37Updated 5 months ago
- Code for Mesh Transformer describes in the EAGLE dataset☆42Updated 9 months ago
- Code for reproducing the experiments in the paper "On Conditional Diffusion Models for PDE Simulations".☆26Updated last year
- PDE-Transformer is a neural network architecture designed to efficiently process and predict the evolution of physical systems described …☆62Updated last month
- ☆51Updated 8 months ago
- [ICLR24] A boundary-embedded neural operator that incorporates complex boundary shape and inhomogeneous boundary values☆29Updated last year
- Code of ICML paper arxiv.org/abs/2302.08105☆14Updated 2 years ago
- ☆12Updated last year
- ☆14Updated last year