Robust Learning in Bayesian Parallel Branching Graph Neural Networks:
The Narrow Width Limit
Robust Learning in Bayesian Parallel Branching Graph Neural Networks:
The Narrow Width Limit
The infinite width limit of random neural networks is known to result in Neural Networks as Gaussian Process (NNGP) (Lee et al. [2018]), characterized by task-independent kernels. It is widely accepted that larger network widths contribute to improved generalization (Park et al. [2019]). However, this work challenges this notion by …