21 citations · 51 across the 9 of their papers we have counts for
7 papers · 1 filter
A Programmer's Guide to Cascaded Adaptive Combiners: Online Learning by Biologically Accurate Models of Multilayer Neuron Networks
Martin Nilsson, Denis Kleyko
Learning in biological multilayer neuronal networks offers insights that extend beyond the classical weighted-sum neuron model commonly used in artificial neural networks. This art…
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…
Variable Binding for Sparse Distributed Representations: Theory and Applications
E. Paxon Frady, Denis Kleyko, Friedrich T. Sommer
Symbolic reasoning and neural networks are often considered incompatible approaches. Connectionist models known as Vector Symbolic Architectures (VSAs) can potentially bridge this…
A theory of sequence indexing and working memory in recurrent neural networks
E. Paxon Frady, Denis Kleyko, Friedrich T. Sommer
To accommodate structured approaches of neural computation, we propose a class of recurrent neural networks for indexing and storing sequences of symbols or analog data vectors. Th…
Neural Distributed Autoassociative Memories: A Survey
V. I. Gritsenko, D. A. Rachkovskij, A. A. Frolov +3
Introduction. Neural network models of autoassociative, distributed memory allow storage and retrieval of many items (vectors) where the number of stored items can exceed the vecto…