Researchers from EPFL and Google Research paired a coarse-grid NCA with a lightweight implicit decoder to render outputs at arbitrary resolution. The decoder maps cell states and local coordinates to appearance attributes, keeping inference parallelizable. Task-specific losses supervise high-resolution outputs for morphogenesis and texture synthesis.
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Summary by ByteBrief
Google's DiffusionGemma trades quality for speed