| license: mit | |
| tags: | |
| - neural-operator | |
| - attention | |
| - operator-learning | |
| arxiv: 2605.31559 | |
| # FuncAttn: Functional Attention | |
| This repository hosts the trained model weights for the PDE benchmarks reported in the paper [Functional Attention: From Pairwise Affinities to Functional Correspondences](https://huggingface.co/papers/2605.31559) (ICML 2026). | |
| - **Project page:** https://xjffff.github.io/funcattn/ | |
| - **Code:** https://github.com/xjffff/funcattn | |
| ## Citation | |
| ```bibtex | |
| @misc{xiao2026functionalattentionpairwiseaffinities, | |
| title={Functional Attention: From Pairwise Affinities to Functional Correspondences}, | |
| author={Jiefang Xiao and Maolin Gao and Simon Weber and Guandao Yang and Daniel Cremers}, | |
| year={2026}, | |
| eprint={2605.31559}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.LG}, | |
| url={https://arxiv.org/abs/2605.31559}, | |
| } | |
| ``` |