28 citations · 28 across the 3 of their papers we have counts for
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cs.LG2025
Slow Feature Analysis on Markov Chains from Goal-Directed Behavior
Merlin Schüler, Eddie Seabrook, Laurenz Wiskott
Slow Feature Analysis is a unsupervised representation learning method that extracts slowly varying features from temporal data and can be used as a basis for subsequent reinforcem…
cs.LG2024
What is the relation between Slow Feature Analysis and the Successor Representation?
Eddie Seabrook, Laurenz Wiskott
Slow feature analysis (SFA) is an unsupervised method for extracting representations from time series data. The successor representation (SR) is a method for representing states in…
cs.LG2022★ 28 cited
A Tutorial on the Spectral Theory of Markov Chains
Eddie Seabrook, Laurenz Wiskott
Markov chains are a class of probabilistic models that have achieved widespread application in the quantitative sciences. This is in part due to their versatility, but is compounde…