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Lorenz Richter

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Preprint Jul 2026

Tensor Train Diffusion: Leveraging Low-Rank Structures for High-Dimensional Score-Based Sampling

This work introduces a novel and efficient solver for the underlying HJB equation based on the functional tensor train (FTT) format, which leverages latent low-rank structures to efficiently approximate high-dimensional functions, enabling both model compression and rapid computation.

Robert Gruhlke, Julius Berner, David Sommer et al. · 0 citations

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