A unified imaging model and weather-prior network restores scenes across multiple adverse conditions by estimating occlusion and transmission from physical particle and scattering effects.
Attention is all you need
2 Pith papers cite this work. Polarity classification is still indexing.
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U2Diffine augments diffusion denoising with negative log-likelihood loss and first-order uncertainty propagation to jointly perform trajectory completion and provide per-state heteroscedastic uncertainty for multi-agent paths.
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Heteroscedastic Diffusion for Multi-Agent Trajectory Modeling
U2Diffine augments diffusion denoising with negative log-likelihood loss and first-order uncertainty propagation to jointly perform trajectory completion and provide per-state heteroscedastic uncertainty for multi-agent paths.