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cs.LG2026
Diffusion Distillation for Efficient Weather Ensembles
Yiming Yang, Valentin Brekke, James Briant +1
Diffusion models generate skillful weather ensembles but require costly iterative sampling. We introduce a supervised energy-distance distillation method that compresses a multi-st…
cs.LG2026
Neural Operator Processes for Probabilistic Operator Learning under Partial Observations
Jose Miguel Lara-Rangel, Serge Guillas
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…
cs.LG2025
Multi-fidelity Batch Active Learning for Gaussian Process Classifiers
Murray Cutforth, Yiming Yang, Tiffany Fan +2
Many science and engineering problems rely on expensive computational simulations, where a multi-fidelity approach can accelerate the exploration of a parameter space. We study eff…