13 citations · 25 across the 8 of their papers we have counts for
5 papers · 1 filter
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…
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…
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…