3 papers
cs.LG2026
Low-power analogue neural networks with trainable nonlinear connections for continuous control
Ian T. Vidamour, Fernando Aguirre, Thomas J. Hayward +13
Physical neural networks promise low-power machine learning by computing directly with analogue device physics, but most architectures force nonlinear device responses to act as sc…
cs.ET2026
When does a control system compute? Digital, mechanical and open-loop systems
Dominic Horsman, Susan Stepney, Tim Clarke +1
Control systems are ubiquitous in modern technology, comprising an engineered plant to be kept within specific, often fine-tuned, limits, and a separate controller that ensures thi…
cs.ET2026
Novel models of computation from novel physical substrates: a bosonic example
Sampreet Kalita, Benjamin W. Butler, Susan Stepney +1
Unconventional physical computing is producing many novel and exotic devices that can potentially be used in a computational mode. Currently, these tend to be used to implement tra…