${{\mathrm {Latent}}Out}$: an unsupervised deep anomaly detection approach exploiting latent space distribution.
Fabrizio AngiulliFabio FassettiLuca FerraginaPublished in: Mach. Learn. (2023)
Keyphrases
- anomaly detection
- latent space
- latent variables
- unsupervised learning
- dimensionality reduction
- low dimensional
- gaussian process
- intrusion detection
- random variables
- parameter space
- generative model
- feature space
- manifold learning
- lower dimensional
- gaussian processes
- matrix factorization
- semi supervised
- high dimensional
- probabilistic latent semantic analysis
- probability distribution
- intrusion detection system
- gaussian process latent variable models
- transfer learning
- probabilistic model
- detect anomalies
- distance metric
- supervised learning
- high dimensional spaces
- pattern recognition
- gaussian mixture
- probability density function
- hyperparameters
- high dimensional data
- computer vision
- model selection
- graphical models
- text mining
- principal component analysis
- pairwise
- image processing