A neural network (cf. Figure 1) can be thought of as a directed acyclic network consisting of

The authors contributed equally to this work 37th Conference on Neural Information Processing Systems (NeurIPS 2023). Developing upper bounds on the generalisation gap, i.e., generalisation bounds has been a longstanding topic in statistical learning.

Specifically, we lay the foundation within the Bayesian framework.

Further, we emphasize the significance of principled regularization of the network parameters and prediction.

In IMP, a multi-component engineering system is subject to a risk of failure due to its components' damage condition.

We compute the convergence rates of the RSVB approximate posterior and the corresponding optimal value.

However, differential privacy's worst-case nature entails scaling such noise to the range of the queries even for

Adversarial attacks have the potential to mislead deep neural network classifiers by introducing slight perturbations.