… Kalman filter to the inference of slow features [12]. Second, … (AIC) to select the number of
slow features in PSFA. In addition, the … The independence between probabilistic slow features …

… slow features (SFs) as temporally correlated LVs are derived using probabilistic SF analysis…
algorithm is proposed to estimate parameters of the probabilistic model, which turns out to be …

… latent feature learning technique for time-varying dynamic phenomena analysis is the so-called
slow feature analysis (SFA). SFA is a deterministic component analysis technique for …

… Slow feature analysis may not extract oscillating patterns when … probabilistic formulation
that extracts slow oscillatory features. … the complex probabilistic slow feature analysis (CPSFA) …

… , probabilistic SFA (PSFA) that extends SFA to a probabilistic … a switching probabilistic slow
feature analysis (switching PSFA… it is possible to extract slowly varying information even when …

… models which are based on Probabilistic Slow Feature Analysis and develop various … we
consider the identification of robust probabilistic slow feature analysis in presence of outliers. A …

… Probabilistic slow feature analysis (PSFA) is an example of such an approach that accounts
… use output information when determining the latent slow features. To address this lacunae, …

… Therefore, this article develops an interval-aware probabilistic slow feature analysis (IA-PSFA)
method along with the corresponding monitoring strategy to address the above problems …

… In this study, a supervised probabilistic slow feature analysis (SPSFA) is proposed to assess
… First, the slow features (SFs) are modeled in state–space form as a serial correlation feature …

… -based probabilistic slow feature analysis, where elastic weight consolidation is employed
to consolidate the previously learned knowledge while extracting multimode slow features. …