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Found 5 papers, 0 papers with code
Compositional Factorization of Visual Scenes with Convolutional Sparse Coding and Resonator Networks
We propose a system for visual scene analysis and recognition based on encoding the sparse, latent feature-representation of an image into a high-dimensional vector that is subsequently factorized to parse scene content.
Computing with Residue Numbers in High-Dimensional Representation
We introduce Residue Hyperdimensional Computing, a computing framework that unifies residue number systems with an algebra defined over random, high-dimensional vectors.
Efficient Decoding of Compositional Structure in Holistic Representations
In particular, we find that the decoding techniques from the sparse coding and compressed sensing literature (rarely used for Hyperdimensional Computing/Vector Symbolic Architectures) are also well-suited for decoding information from the compositional distributed representations.
Integer Factorization with Compositional Distributed Representations
In this paper, we present an approach to integer factorization using distributed representations formed with Vector Symbolic Architectures.
Computing on Functions Using Randomized Vector Representations
By analogy to VSA, we call this new function encoding and computing framework Vector Function Architecture (VFA).
