Fig. 2: VQ-VAE for data compression and restoration. | Nature Communications

Fig. 2: VQ-VAE for data compression and restoration.

From: Multi-modal conditional diffusion model using signed distance functions for metal-organic frameworks generation

Fig. 2

a The architecture of VQ-VAE used within MOFFUSION for latent mapping of SDFs to a lower dimension. The VQ-VAE is composed of encoder and decoder, with a codebook used for vector quantization for mapping into a discrete latent space. b A t-SNE plot for MOFs with the top 10 most frequently appearing topologies. Source data are provided as a Source Data file.

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