NOFE learns continuous function-to-function embeddings via graph kernel operators, outperforming PCA, t-SNE, and UMAP in local structure preservation on function-valued datasets like ERA5 while remaining robust to sampling changes.
Graph Regularized Auto-Encoders for Image Representa- tion.IEEE Transactions on Image Processing, 26(6):2839–2852, June 2017
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NOFE -- Neural Operator Function Embedding
NOFE learns continuous function-to-function embeddings via graph kernel operators, outperforming PCA, t-SNE, and UMAP in local structure preservation on function-valued datasets like ERA5 while remaining robust to sampling changes.