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This paper was accepted at Generative AI and Biology workshop at NeurIPS 2023.

In this paper we tackle the problem of generating a molecule conformation in 3D space given its 2D structure. We approach this problem through the lens of a diffusion model for functions in Riemannian Manifolds. Our approach is simple and scalable, and obtains results that are on par with state-of-the-art while making no assumptions about the explicit structure of molecules.

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