AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work studies nonparametric estimation and forecasting for GARCH-type processes and proposes an iterated neural estimator that alternates between estimating the recursion map and updating the unobserved conditional variances, which is minimax rate-optimal up to logarithmic factors.
ReDiTT, a retrieval augmented conditional diffusion transformer that operates in latent space, is introduced, a retrieval augmented conditional diffusion transformer that operates in latent space that stabilizes long horizon forecasting and improves sample diversity.
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