InvDiff-CGM uses invertible architectures in diffusion and U-Net plus a multi-scale prior injector to construct CGMs with 85% lower peak training memory and 38.02 dB PSNR on RadioMap3DSeer.
RadioDiff- k2: Helmholtz equation informed generative diffusion model for multi-path aware radio map constructio n
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Invertible Diffusion for Low-Memory Channel Gain Map Construction in Wireless Communication Networks
InvDiff-CGM uses invertible architectures in diffusion and U-Net plus a multi-scale prior injector to construct CGMs with 85% lower peak training memory and 38.02 dB PSNR on RadioMap3DSeer.