13 citations · 25 across the 8 of their papers we have counts for
9 papers
Towards a Comprehensive Theory of Reservoir Computing
Denis Kleyko, Christopher J. Kymn, E. Paxon Frady +2
In reservoir computing, an input sequence is processed by a recurrent neural network, the reservoir, which transforms it into a spatial pattern that a shallow readout network can t…
Efficient Hyperdimensional Computing with Modular Composite Representations
Marco Angioli, Christopher J. Kymn, Antonello Rosato +3
The modular composite representation (MCR) is a computing model that represents information with high-dimensional integer vectors using modular arithmetic. Originally proposed as a…
High-resolution spatial memory requires grid-cell-like neural codes
Madison Cotteret, Christopher J. Kymn, Hugh Greatorex +3
Continuous attractor networks (CANs) are widely used to model how the brain temporarily retains continuous behavioural variables via persistent recurrent activity, such as an anima…
Binding in hippocampal-entorhinal circuits enables compositionality in cognitive maps
Christopher J. Kymn, Sonia Mazelet, Anthony Thomas +4
We propose a normative model for spatial representation in the hippocampal formation that combines optimality principles, such as maximizing coding range and spatial information pe…
Compositional Factorization of Visual Scenes with Convolutional Sparse Coding and Resonator Networks
Christopher J. Kymn, Sonia Mazelet, Annabel Ng +2
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 subsequ…
Computing with Residue Numbers in High-Dimensional Representation
Christopher J. Kymn, Denis Kleyko, E. Paxon Frady +4
We introduce Residue Hyperdimensional Computing, a computing framework that unifies residue number systems with an algebra defined over random, high-dimensional vectors. We show ho…
Efficient Decoding of Compositional Structure in Holistic Representations
Denis Kleyko, Connor Bybee, Ping-Chen Huang +4
We investigate the task of retrieving information from compositional distributed representations formed by Hyperdimensional Computing/Vector Symbolic Architectures and present nove…
Integer Factorization with Compositional Distributed Representations
Denis Kleyko, Connor Bybee, Christopher J. Kymn +5
In this paper, we present an approach to integer factorization using distributed representations formed with Vector Symbolic Architectures. The approach formulates integer factoriz…
Computing on Functions Using Randomized Vector Representations
E. Paxon Frady, Denis Kleyko, Christopher J. Kymn +2
Vector space models for symbolic processing that encode symbols by random vectors have been proposed in cognitive science and connectionist communities under the names Vector Symbo…