Related papers: Constrained Synthesis with Projected Diffusion Models

Constrained Synthesis with Projected Diffusion Models

URL: http://arxiv.org/abs/2402.03559v3
Date: Fri, 01 Nov 2024 20:15:18 GMT
Title: Constrained Synthesis with Projected Diffusion Models
Authors: Jacob K Christopher, Stephen Baek, Ferdinando Fioretto,
Abstract summary: This paper introduces an approach to generative diffusion processes the ability to satisfy and certify compliance with constraints and physical principles. The proposed method recast the traditional process of generative diffusion as a constrained distribution problem to ensure adherence to constraints.
Score: 47.56192362295252
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Abstract: This paper introduces an approach to endow generative diffusion processes the ability to satisfy and certify compliance with constraints and physical principles. The proposed method recast the traditional sampling process of generative diffusion models as a constrained optimization problem, steering the generated data distribution to remain within a specified region to ensure adherence to the given constraints. These capabilities are validated on applications featuring both convex and challenging, non-convex, constraints as well as ordinary differential equations, in domains spanning from synthesizing new materials with precise morphometric properties, generating physics-informed motion, optimizing paths in planning scenarios, and human motion synthesis.

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