Network complexity and computational efficiency have become increasingly...
Deep neural network ensembles that appeal to model diversity have been u...
Ising models originated in statistical physics and are widely used in
mo...
Sparse deep neural networks have proven to be efficient for predictive m...
For many decades now, Bayesian Model Averaging (BMA) has been a popular
...
Bayesian neural network models (BNN) have re-surged in recent years due ...
This article introduces a Bayesian neural network estimation method for
...
Mathematical models implemented on a computer have become the driving fo...
Despite the popularism of Bayesian neural networks in recent years, its ...
Whether an extreme observation is an outlier or not, depends strongly on...
We introduce a trimmed version of the Hill estimator for the index of a
...