2 papers
cs.LG2025
Scaling of hardware-compatible perturbative training algorithms
Bakhrom G. Oripov, Andrew Dienstfrey, Adam N. McCaughan +1
In this work, we explore the capabilities of multiplexed gradient descent (MGD), a scalable and efficient perturbative zeroth-order training method for estimating the gradient of a…
cs.ET2025
Roadmap on Neuromorphic Photonics
Daniel Brunner, Bhavin J. Shastri, Mohammed A. Al Qadasi +147
This roadmap consolidates recent advances while exploring emerging applications, reflecting the remarkable diversity of hardware platforms, neuromorphic concepts, and implementatio…