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Capital Fund Management, Paris, France
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Uncover hidden relationships in your diffusion model's learned distribution by tracing paths between samples with a new string method framework, revealing realistic morphing sequences and protein transition pathways.
Skip the GANs: this kernel method generates complex data like financial time series and images without any training, just by solving linear systems.
Escape the MCMC slowdown: this diffusion-based approach efficiently samples maximum entropy distributions by directly guiding moments, offering a practical alternative for high-dimensional uncertainty quantification.
