2 papers
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…