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#machine learning Preprint Sep 2026

A Splitting Method for SDE Terminal-Law Estimation

In many settings involving stochastic differential equations, including in diffusion based generative AI, our aim is to accurately generate samples from a terminal distribution. Typically, this is done by generating i.i.d. samples of diffusion paths. Given a fixed simulation budget, a reasonable way to gain efficiency...

Rushil Gupta, S. Juneja · 0 citations
#machine learning Preprint Sep 2026

Steering Diffusion Priors with Sparse Observations for High-Resolution Temperature Downscaling

Local heatwave hazard depends on fine-scale air temperature, but ground stations are sparse and reanalysis products such as ERA5 cannot resolve the terrain and land-surface contrasts that shape real heat exposure. We present a conditional diffusion emulator for high-resolution 2-m temperature downscaling, conditioned o...

Anirudh Avireddy, Manmeet Singh, Shivanshi Singh et al. · 0 citations

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