Climate change has been a challenging and urgent research problem for many related research fields. Climate change trends and patterns are complex, which may involve many factors a...
We explore a periodic analysis in the context of unobserved components time series models that decompose time series into components of interest such as trend, seasonal and irregu...
A recently proposed Bayesian multiscale tool for exploratory analysis of time series data is reconsidered and umerous important improvements are suggested. The improvements are in...
: Temporal data mining is concerned with the analysis of temporal data and finding temporal patterns, regularities, trends, clusters in sets of temporal data. Wavelet transform pro...
In this paper we describe an interdisciplinary collaboration between researchers in machine learning and oceanography. The collaboration was formed to study the problem of open oc...
Joshua M. Lewis, Pincelli M. Hull, Kilian Q. Weinb...