We introduce a generalized information criterion that contains other
wel...
We design a Universal Automatic Elbow Detector (UAED) for deciding the
e...
In the last decade, soundscapes have become one of the most active topic...
The application of Bayesian inference for the purpose of model selection...
This survey gives an overview of Monte Carlo methodologies using surroga...
Statistical signal processing applications usually require the estimatio...
We propose a novel adaptive importance sampling scheme for Bayesian inve...
Monte Carlo methods are the standard procedure for estimating complicate...
Understanding systems by forward and inverse modeling is a recurrent top...
Numerical integration and emulation are fundamental topics across scient...
Importance Sampling (IS) is a well-known Monte Carlo technique that
appr...
Monte Carlo (MC) methods are widely used for Bayesian inference and
opti...
Monte Carlo methods represent the "de facto" standard for approximating
...
Multi-output inference tasks, such as multi-label classification, have b...
In this work, we introduce a novel class of adaptive Monte Carlo methods...