Kellian Cottart

Kellian Cottart

Doctoral student in Bayesian AI and Neuromorphic engineering at Université Paris-Saclay | Data Sciences at Ecole Polytechnique (IPP2023) | Engineer's degree at Ecole Centrale d'Electronique

Publications

For more information, check my Google Scholar profile.

Journal Papers

Bayesian continual learning and forgetting in neural networks

Published in Nature Communications, 2025

We introduce Metaplasticity from Synaptic Uncertainty (MESU), a Bayesian update rule that scales each parameter’s learning by its uncertainty, enabling a principled combination of learning and forgetting without explicit task boundaries.

Recommended citation: Bonnet, Djohan, et al. "Bayesian continual learning and forgetting in neural networks." Nature Communications 16.1 (2025): 9614.
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Dynamic Control of Weight-Update Linearity in Magneto-Ionic Synapses

Published in Nanoletters, 2025

We demonstrate that magneto-ionic devices can perform as synaptic elements with dynamically tunable depression linearity controlled by an external magnetic field, a functionality reminiscent of neuromodulation in biological systems.

Recommended citation: Bernard, Guillaume, et al. "Dynamic control of weight-update linearity in magneto-ionic synapses." Nano Letters 25.4 (2025): 1443-1450. doi: 10.1021/acs.nanolett.4c05247
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A unified method to generate representative volume elements with tailored random fibre arrangements to estimate the shear and transverse behaviours of unidirectional continuous fibres composite plies

Published in Journal Of Composite Materials, 2024

Different microstructures with or without clusters of fibres (resulting from manufacturing processes) are necessary to quantify the mechanical variability. The variability of the microstructures is characterised by the variation of the arrangement, the volume fraction and the misalignment of the fibres.

Recommended citation: Mechin P-Y, Borras A, Cottart K, Keryvin V. A unified method to generate representative volume elements with tailored random fibre arrangements to estimate the shear and transverse behaviours of unidirectional continuous fibres composite plies. Journal of Composite Materials. 2024;0(0). doi: 10.1177/00219983241300144
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