3 papers
cs.ET2024
Nonideality-aware training makes memristive networks more robust to adversarial attacks
Dovydas Joksas, Luis Muñoz-González, Emil Lupu +1
Neural networks are now deployed in a wide number of areas from object classification to natural language systems. Implementations using analog devices like memristors promise bett…
cs.ET2023★ 1 cited
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…
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…