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Representation Learning in Continuous-Time Score-Based Generative Models
Score-based methods represented as stochastic differential equations on a continuous time domain have recently proven successful as a non-adversarial generative model.
Diffusion-Based Representation Learning
In contrast, the introduced diffusion-based representation learning relies on a new formulation of the denoising score matching objective and thus encodes the information needed for denoising.
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