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A. Mehonic

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author1

Across the 2 of 3 papers where every author was matched, so the position is known.

fields
  • cs.ET2
  • cond-mat.mtrl-sci1

identity via Semantic Scholar / OpenAlex

most citedMemristors -- from In-memory computing, Deep Learning Acceleration, Spiking Neural Networks, to the Future of Neuromorphic and Bio-inspired Computing

1 citations · 1 across the 2 of their papers we have counts for

collaborators

3 papers

cond-mat.mtrl-sci2020

Nanoscale plasticity and neuromorphic dynamics in silicon suboxide RRAM

Mark Buckwell, Wing Hung Ng, Daniel John Mannion +3

Resistive random-access memories, also known as memristors, whose resistance can be modulated by the electrically driven formation and disruption of conductive filaments within an…

cs.ET2020★ 1 cited

Memristors -- from In-memory computing, Deep Learning Acceleration, Spiking Neural Networks, to the Future of Neuromorphic and Bio-inspired Computing

Adnan Mehonic, Abu Sebastian, Bipin Rajendran +3

Machine learning, particularly in the form of deep learning, has driven most of the recent fundamental developments in artificial intelligence. Deep learning is based on computatio…

cs.ET2019

Committee machines -- a universal method to deal with non-idealities in memristor-based neural networks

D. Joksas, P. Freitas, Z. Chai +7

Artificial neural networks are notoriously power- and time-consuming when implemented on conventional von Neumann computing systems. Consequently, recent years have seen an emergen…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.