3 papers
cs.NE2025
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…
cs.LG2025
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…
cs.NE2025
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…