Equivalent Wishart Ansatz for kernel renormalization in Bayesian MLPs and CNNs in the proportional regime, with tests showing good agreement on benchmarks.
Mitigating the curse of detail: Scaling arguments for feature learning and sample complexity,
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Kernel Renormalization in Bayesian Deep Neural Networks: the Equivalent Wishart Ansatz in the Proportional Regime
Equivalent Wishart Ansatz for kernel renormalization in Bayesian MLPs and CNNs in the proportional regime, with tests showing good agreement on benchmarks.