In the current landscape of deep learning research, there is a predominant emphasis on
achieving high predictive accuracy in supervised tasks involving large image and language …

Motivated by the sensitivity-based importance score of the adaptive low-rank adaptation
(AdaLoRA), we utilize more theoretically supported metrics, including the signal-to-noise …

In this paper, we present Partially Stochastic Infinitely Deep Bayesian Neural Networks, a
novel family of architectures that integrates partial stochasticity into the framework of …