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Exploring the Intrinsic Geometry of Diffusion Models with Constrained Inverse Kinematics
Recent studies suggest that diffusion models can recover geometric structure in the data they are trained on, yet the supporting evidence has so far come mostly from natural-image data, where the underlying geometry itself is unknown. We study this question in a setting where the geometry is analyti
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