AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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A stopgrad regression principle is introduced, which identifies a general template for stopgrad objectives with a closed-form characterization of stationary points and their uniqueness, unifying stopgrad objectives for flow maps, reinforcement learning, and diffusion samplers.
SGFlow is introduced, an approach for learning flow maps that bypasses explicit invertibility constraints and expensive differentiation through model iteration and trains a model to compute both the ODE solutions and the implied velocity from scratch by following non-conservative dynamics with a stationary point at the...
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