4 papers
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…
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…
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…
Sequential Design for Simulators with Sharp Variations via Deep Gaussian Process Gradients
Yiming Yang, Deyu Ming, Serge Guillas
Deep Gaussian Processes (DGPs) compose Gaussian Process (GP) layers to warp inputs, improving the emulation of computer simulators with nonstationary input-output mappings. While g…