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Theoretical guarantees in KL for Diffusion Flow Matching
A significant task in statistics and machine learning currently revolves around generating samples from a target distribution that is only accessible via a dataset.
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- Information Technology > Artificial Intelligence > Vision (1.00)
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- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (0.93)
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Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling
To solve this optimization, we propose a simulation-free training objective with a model parameterization that imposes the desired boundary conditions by design.
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Stochastic Optimal Control for Diffusion Bridges in Function Spaces Byoungwoo Park
In this paper, we present a theory of stochastic optimal control (SOC) tailored to infinite-dimensional spaces, aiming to extend diffusion-based algorithms to function spaces. Specifically, we demonstrate how Doob's
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