activity
20242026
most citedA feature-based information-theoretic approach for detecting interpretable, long-timescale pairwise interactions from time series

3 citations · 4 across the 7 of their papers we have counts for

collaborators
Showing 2026 · physics.data-anShow all

2 papers · 2 filters

physics.data-an2026

Parameter inference from a non-stationary unknown process using statistical feature-based slow feature analysis

Kieran S. Owens, Masako Tamaki, Ben D. Fulcher

Non-stationary phenomena are ubiquitous, with examples to be found in climatological measurements, brain activity, and the behavior of financial markets. Starting with a time serie…

physics.data-an2026

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…