AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Flow Matching (FM) learns a velocity field whose ODE transports a simple source distribution to a target law. Existing finite-sample theory largely treats ambient-space regularity or data supported exactly on low-dimensional sets. We study linear FM under a noisy latent-generator model, where a low-dimensional H\"older...
We study high-dimensional finite-horizon Hamilton--Jacobi--Bellman equations for controlled diffusions with uniformly elliptic, state-dependent diffusion coefficients. Motivated by the need for a rigorous analytical framework that explains neural-network approximation in high-dimensional stochastic control, we formulat...
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