A standardized pipeline converts time series to graphs, computes persistence diagrams, and extracts features that classify UCR benchmarks, with diffusion distance outperforming shortest-path metrics and performance varying by graph type.
Complex network from time series based on phase space reconstruction.Chaos, 19(3):033137
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
math.AT 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Persistent Homology of Time Series through Complex Networks
A standardized pipeline converts time series to graphs, computes persistence diagrams, and extracts features that classify UCR benchmarks, with diffusion distance outperforming shortest-path metrics and performance varying by graph type.