115 citations · 137 across the 5 of their papers we have counts for
5 papers
Memristive-Friendly Hadamard Reservoir Computing: Structured, Multiplier-Free Recurrences at Scale
Andrea Ceni, Gianluca Milano, Carlo Ricciardi +1
Reservoir Computing (RC) designs Recurrent Neural Networks around a fixed, i.e., untrained, recurrent layer, and is a natural candidate for neuromorphic hardware. Memristive-friend…
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…
Mean field theory of self-organizing memristive connectomes
Francesco Caravelli, Gianluca Milano, Carlo Ricciardi +1
Biological neuronal networks are characterized by nonlinear interactions and complex connectivity. Given the growing impetus to build neuromorphic computers, understanding physical…
2022 Roadmap on Neuromorphic Computing and Engineering
Dennis V. Christensen, Regina Dittmann, Bernabé Linares-Barranco +56
Modern computation based on the von Neumann architecture is today a mature cutting-edge science. In the Von Neumann architecture, processing and memory units are implemented as sep…
Self-organizing memristive nanowire networks with structural plasticity emulate biological neuronal circuits
Gianluca Milano, Giacomo Pedretti, Matteo Fretto +5
Acting as artificial synapses, two-terminal memristive devices are considered fundamental building blocks for the realization of artificial neural networks. Organized into large ar…