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Found 6 papers, 2 papers with code
Dynamic Conditional Optimal Transport through Simulation-Free Flows
We study the geometry of conditional optimal transport (COT) and prove a dynamical formulation which generalizes the Benamou-Brenier Theorem.
Precipitation Downscaling with Spatiotemporal Video Diffusion
In climate science and meteorology, high-resolution local precipitation (rain and snowfall) predictions are limited by the computational costs of simulation-based methods.
Functional Flow Matching
We propose Functional Flow Matching (FFM), a function-space generative model that generalizes the recently-introduced Flow Matching model to operate in infinite-dimensional spaces.
Diffusion Generative Models in Infinite Dimensions
We generalize diffusion models to operate directly in function space by developing the foundational theory for such models in terms of Gaussian measures on Hilbert spaces.
Combining Human Predictions with Model Probabilities via Confusion Matrices and Calibration
An increasingly common use case for machine learning models is augmenting the abilities of human decision makers.
Differentially Private Language Models Benefit from Public Pre-training
Language modeling is a keystone task in natural language processing.
