Diffusion probabilistic models enhance variational autoencoder for crystal structure generative modeling

Research article (Scientific Reports, 2024) · cited 23× · AI/ML
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Diffusion probabilistic models enhance variational autoencoder for crystal structure generative modeling

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Diffusion probabilistic models enhance variational autoencoder for crystal structure generative modeling is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Diffusion probabilistic models enhance variational autoencoder for crystal structure generative modeling. Retrieved May 24, 2026, from https://4ort.xyz/entity/diffusion-probabilistic-models-enhance-variational-autoencoder-for-crystal-structure-generative-modeling
MLA “Diffusion probabilistic models enhance variational autoencoder for crystal structure generative modeling.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/diffusion-probabilistic-models-enhance-variational-autoencoder-for-crystal-structure-generative-modeling.
BibTeX @misc{4ortxyz_diffusion-probabilistic-models-enhance-variational-autoencoder-for-crystal-structure-generative-modeling_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Diffusion probabilistic models enhance variational autoencoder for crystal structure generative modeling}}, year = {2026}, url = {https://4ort.xyz/entity/diffusion-probabilistic-models-enhance-variational-autoencoder-for-crystal-structure-generative-modeling}, note = {Accessed: 2026-05-24}}
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