Learned Kalman Filtering in Latent Space with High-Dimensional Data.
Itay BuchnikDamiano StegerGuy RevachRuud J. G. van SlounTirza RouttenbergNir ShlezingerPublished in: ICASSP (2023)
Keyphrases
- latent space
- kalman filtering
- high dimensional data
- low dimensional
- dimensionality reduction
- lower dimensional
- kalman filter
- high dimensional
- manifold learning
- high dimensional spaces
- nearest neighbor
- dimension reduction
- high dimensionality
- similarity search
- subspace clustering
- data points
- particle filtering
- feature space
- data analysis
- original data
- data sets
- nonlinear dimensionality reduction
- sparse representation
- dimensional data
- principal component analysis
- gaussian process
- parameter space
- gaussian processes
- euclidean space
- generative model
- matrix factorization
- distance function
- latent variables
- machine learning
- active learning
- high resolution
- pattern recognition
- probabilistic latent semantic analysis
- computer vision