4 citations · 4 across the 2 of their papers we have counts for
3 papers
Interpretable model-free inference of parametric variation across time-series data through large-scale feature extraction
Ben D. Fulcher, Carl H. Lubba, Giorgio F. Gilestro +2
Here we address the problem of estimating the dimensionality and nature of parametric variation in an unknown generative process directly from time-series data, without specifying…
CompEngine: a self-organizing, living library of time-series data
Ben D. Fulcher, Carl H. Lubba, Sarab S. Sethi +1
Modern biomedical applications often involve time-series data, from high-throughput phenotyping of model organisms, through to individual disease diagnosis and treatment using biom…
catch22: CAnonical Time-series CHaracteristics
Carl H Lubba, Sarab S Sethi, Philip Knaute +3
Capturing the dynamical properties of time series concisely as interpretable feature vectors can enable efficient clustering and classification for time-series applications across…