In this paper, we study the post-hoc calibration of modern neural networ...
This work introduces the Efficient Transformed Gaussian Process (ETGP), ...
Gaussian Processes (GPs) can be used as flexible, non-parametric functio...
Deep Neural Networks (DNN) represent the state of the art in many tasks....
This paper explores several strategies for Forensic Voice Comparison (FV...
Deep Neural Networks (DNNs) have achieved state-of-the-art accuracy
perf...
The goal of this paper is to deal with a data scarcity scenario where de...