Finetuning-Free Diffusion Model with Adaptive Constraint Guidance for Inorganic Crystal Structure Generation

arXiv:2604.13354v2 Announce Type: replace-cross Abstract: The discovery of inorganic crystal structures with targeted properties is a significant challenge in materials science. Generative models, especially state-of-the-art diffusion models, offer the promise of modeling complex data distributions and proposing novel, realistic samples. However, current generative AI models still struggle to produce diverse, original, and reliable structures of experimentally achievable materials suitable for high-stakes applications. In this work, we propose a generative machine learning framework based on d

Source: arXiv cs.AI — read the full report at the original publisher.

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