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Found 4 papers, 2 papers with code
Enhancing Score-Based Sampling Methods with Ensembles
We introduce ensembles within score-based sampling methods to develop gradient-free approximate sampling techniques that leverage the collective dynamics of particle ensembles to compute approximate reverse diffusion drifts.
Easing Color Shifts in Score-Based Diffusion Models
Generated images of score-based models can suffer from errors in their spatial means, an effect, referred to as a color shift, which grows for larger images.
Unpaired Downscaling of Fluid Flows with Diffusion Bridges
We present a method to downscale idealized geophysical fluid simulations using generative models based on diffusion maps.
Unsupervised Discovery of El Nino Using Causal Feature Learning on Microlevel Climate Data
We show that the climate phenomena of El Nino and La Nina arise naturally as states of macro-variables when our recent causal feature learning framework (Chalupka 2015, Chalupka 2016) is applied to micro-level measures of zonal wind (ZW) and sea surface temperatures (SST) taken over the equatorial band of the Pacific Ocean.
