One of the most important challenges for the researchers in the 21st Century is related to global heating and climate change that can have as consequence the intensiļ¬cation of na...
Luciana A. S. Romani, Ana Maria Heuminski de &Aacu...
We combine Bayesian online change point detection with Gaussian processes to create a nonparametric time series model which can handle change points. The model can be used to loca...
In time series analysis, inference about causeeffect relationships among multiple times series is commonly based on the concept of Granger causality, which exploits temporal struc...
An important task in exploration of data about phenomena and processes that develop over time is detection of significant changes that happened to the studied phenomenon. Our rese...
Gennady L. Andrienko, Natalia V. Andrienko, Martin...
We propose a scalable and efficient parameterized block-based statistical static timing analysis algorithm incorporating both Gaussian and non-Gaussian parameter distributions, ca...