AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work proposes CLaST, a VAE framework for probabilistic multivariate time series forecasting that learns embeddings that preserve contextual similarity between observations through the authors' contrastive loss function.
DecoVAE is proposed, a lightweight interpretable trend-seasonal VAE framework that explicitly decomposes time series into trend and seasonal components by applying domain-specific inductive biases.
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