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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.
