Author

Aliaksandr Hubin

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#machine learning Preprint Sep 2026

Benchmarking the Connectomes of Caenorhabditis elegans within the Reservoir Computing Framework

The results show that the biological wiring and a bio-informed configuration of input and output nodes of the reservoirs do not necessarily lead to better performance and it becomes clear that the results depend a lot on the configuration of the reservoir and the way the connectome has been derived from the organism.

F. Reimers, O. H. Ramstad, Aliaksandr Hubin et al. · 0 citations

#machine learning Preprint Sep 2026

Exploring napping paradigm for Recurrent Spiking Neural Networks

This paper investigates the hypothesis that a biologically inspired micro-sleep paradigm, napping -- combining proportional weight scaling with continuous stochastic membrane activity -- can replicate the stability of normalization while shedding model complexity.

A. Massey, Stefano Nichele, Aliaksandr Hubin · 0 citations