AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Simulation-free training of latent Stochastic Differential Equations (SDEs) relies on a variational posterior process whose one-time marginals are tractable, typically Gaussian. Such marginals, however, do not determine the underlying dynamics: many processes share the same marginals while differing in their temporal s...
Based on this formulation of flow matching as variational inference, CatFlow is developed, a flow matching method for categorical data that is easy to implement, computationally efficient, and achieves strong results on graph generation tasks.
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