18 citations · 59 across the 6 of their papers we have counts for
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cond-mat.dis-nn2025★ 1 cited
Self-Organising Memristive Networks as Physical Learning Systems
Francesco Caravelli, Gianluca Milano, Adam Z. Stieg +3
Learning with physical systems is an emerging paradigm that seeks to harness the intrinsic nonlinear dynamics of physical substrates for learning. The impetus for a paradigm shift…
cond-mat.dis-nn2020★ 14 cited
Harnessing adaptive dynamics in neuro-memristive nanowire networks for transfer learning
Ruomin Zhu, Joel Hochstetter, Alon Loeffler +5
Nanowire networks (NWNs) represent a unique hardware platform for neuromorphic information processing. In addition to exhibiting synapse-like resistive switching memory at their cr…