Joint Inference for Neural Network Depth and Dropout Regularization

2 code implementations • NeurIPS 2021 • Kishan K C, Rui Li, MohammadMahdi Gilany

We propose a unified Bayesian model selection method to jointly infer the most plausible network depth warranted by data, and perform dropout regularization simultaneously.

Continual Learning Model Selection