637 citations · 719 across the 8 of their papers we have counts for
8 papers
Roadmap to Neuromorphic Computing with Emerging Technologies
Adnan Mehonic, Daniele Ielmini, Kaushik Roy +50
The roadmap is organized into several thematic sections, outlining current computing challenges, discussing the neuromorphic computing approach, analyzing mature and currently util…
Emerging Nonvolatile Memories for Machine Learning
Adnan Mehonic, Dovydas Joksas
Digital computers have been getting exponentially faster for decades, but huge challenges exist today. Transistor scaling, described by Moore's law, has been slowing down over the…
Memristive, Spintronic, and 2D-Materials-Based Devices to Improve and Complement Computing Hardware
Dovydas Joksas, AbdulAziz AlMutairi, Oscar Lee +5
In a data-driven economy, virtually all industries benefit from advances in information technology -- powerful computing systems are critically important for rapid technological pr…
Nonideality-Aware Training for Accurate and Robust Low-Power Memristive Neural Networks
Dovydas Joksas, Erwei Wang, Nikolaos Barmpatsalos +4
Recent years have seen a rapid rise of artificial neural networks being employed in a number of cognitive tasks. The ever-increasing computing requirements of these structures have…
Brain-inspired computing: We need a master plan
Adnan Mehonic, Anthony J Kenyon
New computing technologies inspired by the brain promise fundamentally different ways to process information with extreme energy efficiency and the ability to handle the avalanche…
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…
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…
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…