TechGoogle Researchabout 2 hours ago
Towards demystifying the creativity of diffusion models
1 min read
A paper presented at ICLR 2026 shows that diffusion model creativity is a mathematical consequence of score smoothing. Neural network regularization blurs the learned score function, causing denoising to interpolate between training data points along the data manifold. This produces novel, realistic outputs rather than memorized copies.
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