AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work introduces Masked Neural Causal Models (NCMs), a provably expressive nonparametric framework for simulating and bounding interventional queries over all models compatible with a given CPDAG given observational data, and gives an optimization objective in the space of masked NCMs that asymptotically recovers t...
Counterfactual Shapley Credit Assignment is introduced, a novel framework grounded in causal theory that attributes credit and blame via the Counterfactual Shapley Value ($\phi$-value) to enhance temporal credit assignment across three critical dimensions: sparse causality, high stochasticity, and delayed rewards, all...
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