arXiv AI By Bata Vasic, Bane Vasic

Energy-Conditioned Noise Schedule and Whitening for Spectral Diffusion

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The paper proposes an energy‑adaptive noise scheduling and whitening strategy for transform‑domain diffusion models. By aligning the forward diffusion process with the spectral energy distribution of natural images, the method jointly modulates injected noise based on individual transform coefficient energy and an image‑dependent energy path over diffusion time. Experiments on CIFAR‑10 show that this approach reduces the Fréchet Inception Distance from 142.48 to 100.45 for a compact DCT‑diff U‑Net variant.

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arXiv Machine Learning
2d ago

Disentangling Total-Variance and Signal-to-Noise-Ratio Improves Diffusion Models

The paper introduces a total‑variance/signal‑to‑noise‑ratio (TV/SNR) framework that allows independent control of TV and SNR in diffusion models. By replacing exponentially exploding TV schedules with constant TV while keeping the SNR schedule, the authors achieve consistent improvements in generation efficiency. The approach generalizes the SNR schedule from optimal transport flow matching and works across various reverse diffusion solvers, reducing the search space to two interpretable parameters for robust sampling in scientific applications such as molecular structure generation.

By Khaled Kahouli, Winfried Ripken, Stefan Gugler, Oliver T. Unke, Klaus-Robert M\"{u}ller, Shinichi Nakajima