MIT Researchers Introduce Restart Sampling For Improving Generative Processes

Differential equation-based deep generative models have recently emerged as potent modeling tools for high-dimensional data in fields ranging from image synthesis to biology. These models solve differential equations iteratively in reverse, eventually transforming a basic distribution (such as a Gaussian in diffusion models) into a complicated data distribution. Studies have categorized prior samplers that can […]

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