3 citations · 4 across the 7 of their papers we have counts for
3 papers · 1 filter
Using matrix-product states for time-series machine learning
Joshua B. Moore, Hugo P. Stackhouse, Ben D. Fulcher +1
Matrix-product states (MPS) have proven to be a versatile ansatz for modeling quantum many-body physics. For many applications, and particularly in one-dimension, they capture rele…
Parameter inference from a non-stationary unknown process
Kieran S. Owens, Ben D. Fulcher
Non-stationary systems are found throughout the world, from climate patterns under the influence of variation in carbon dioxide concentration, to brain dynamics driven by ascending…
A feature-based information-theoretic approach for detecting interpretable, long-timescale pairwise interactions from time series
Aria Nguyen, Oscar McMullin, Joseph T. Lizier +1
Quantifying relationships between components of a complex system is critical to understanding the rich network of interactions that characterize the behavior of the system. Traditi…