Hugging Face Trending Papers June 22, 2026

Neural Operator Processes for Probabilistic Operator Learning under Partial Observations

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Neural operators learn mappings between function spaces, but are typically developed with dense input-output training fields and fully observed inputs at inference. Many scientific problems require instead predicting solution fields from sparse, irregular, or partial observations under uncertainty.

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