AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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A comprehensive review of AI-enabled O-RAN systems and a taxonomy of AI approaches for O-RAN, covering machine learning, deep reinforcement learning (DRL), digital-twin-assisted optimization, and emerging foundation-model-based architectures are presented.
This paper proposes a novel framework for multivariate time-series anomaly detection that leverages adversarial learning and contrastive loss within a sequence-based Variational Autoencoder (VAE) architecture, and introduces encoder and decoder adaptor layers that align feature distributions across domains while preser...
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