AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Perceptive General Motion Tracking pipeline for humanoid robots that learns terrain adaptation from independently selected motion references and terrains, providing a unified policy for terrain-adaptive locomotion, diverse whole-body behaviors, and teleoperation in complex environments.
SSP-DMGTimeNet, a physics-constrained learning framework for spatiotemporal trajectory prediction of vehicle platoons, combines multi-scale temporal representations with cross-vehicle interaction features to capture complex and time-varying platoon dynamics.
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