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arXiv · 2505.12412

Training Latent Diffusion Models with Interacting Particle Algorithms

Tim Y. J. Wang·Juan Kuntz·O. Deniz Akyildiz
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Abstract

We introduce a novel particle-based algorithm for end-to-end training of latent diffusion models. We reformulate the training task as minimizing a free energy functional and obtain a gradient flow that does so. By approximating the latter with a system of interacting particles, we obtain the algorithm, which we underpin theoretically by providing error guarantees. The novel algorithm compares favorably in experiments with previous particle-based methods and variational inference analogues.

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Tim Y. J. Wang, Juan Kuntz, O. Deniz Akyildiz. 2025-05-18. Training Latent Diffusion Models with Interacting Particle Algorithms. https://arxiv.org/abs/2505.12412

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