LatentStealth is a latent-space optimization method that produces imperceptible yet effective adversarial attacks on expressive human pose and shape estimation models using few output queries.
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NC-Diffusion matches quantization noise to the diffusion forward process, adds an adaptive frequency filter and zero-shot enhancement, and reports superior fidelity on benchmarks.
A diffusion-based generative ML paradigm is introduced to proactively generate and rank high-risk contingencies for voltage stability using physical information from operating points, with experiments on IEEE-6 to IEEE-118 systems.
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LatentStealth: Unnoticeable and Efficient Adversarial Attacks on Expressive Human Pose and Shape Estimation
LatentStealth is a latent-space optimization method that produces imperceptible yet effective adversarial attacks on expressive human pose and shape estimation models using few output queries.
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A Noise Constrained Diffusion (NC-Diffusion) Framework for High Fidelity Image Compression
NC-Diffusion matches quantization noise to the diffusion forward process, adds an adaptive frequency filter and zero-shot enhancement, and reports superior fidelity on benchmarks.
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A Diffusion-based Generative Machine Learning Paradigm for Dynamic Contingency Screening
A diffusion-based generative ML paradigm is introduced to proactively generate and rank high-risk contingencies for voltage stability using physical information from operating points, with experiments on IEEE-6 to IEEE-118 systems.