Researchers from the University of Wisconsin-Madison Challenge the Efficacy of Score-based Generative Models: A Surprising Revelation of Gaussian Mimicry in High-Quality Data Generation

Score-based Generative Models (SGMs) are a prominent approach in generative modeling, celebrated for their capacity to produce high-quality samples from intricate, high-dimensional data distributions. This method has garnered empirical success and is bolstered by robust theoretical convergence properties. Notably, it has been established that SGMs can generate samples from a distribution closely approximating the ground […]

The post Researchers from the University of Wisconsin-Madison Challenge the Efficacy of Score-based Generative Models: A Surprising Revelation of Gaussian Mimicry in High-Quality Data …

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