Perspectives of the high-dimensional dynamics of neural microcircuits from the point of view of low-dimensional readouts.
Stefan HäuslerHenry MarkramWolfgang MaassPublished in: Complex. (2003)
Keyphrases
- low dimensional
- high dimensional
- high dimensional data
- dimensionality reduction
- manifold learning
- network architecture
- dimension reduction
- data points
- euclidean space
- feature space
- input space
- neural network
- vector space
- recurrent networks
- high dimensionality
- similarity search
- lower dimensional
- gaussian process latent variable models
- high dimensions
- multi dimensional
- neural mechanisms
- dynamic model
- nonlinear dimensionality reduction
- principal component analysis
- linear subspace
- high dimensional spaces
- high dimensional data space
- high dimension
- multidimensional scaling
- neural model
- pattern recognition
- nearest neighbor
- low dimensional spaces
- sparse coding
- hamming space
- graph embedding
- dynamical systems
- kernel function
- pairwise
- feature extraction
- computer vision