Multiplexed gradient descent: Fast online training of modern datasets on hardware neural networks without backpropagation. - Adam N. McCaughan; Bakhrom G. Oripov; Natesh Ganesh; Sae Woo Nam; Andrew M. Dienstfrey; Sonia M. Buckley (CoRR, 2023)

Superconducting Heater Cryotron-Based Reconfigurable Logic Towards Cryogenic IC Camouflaging. - Shamiul Alam; Dana S. Rampini; Bakhrom G. Oripov; Adam N. McCaughan; Ahmedullah Aziz (CoRR, 2023)

Machine Learning-powered Compact Modeling of Stochastic Electronic Devices using Mixture Density Networks. - Jack Hutchins; Shamiul Alam; Dana S. Rampini; Bakhrom G. Oripov; Adam N. McCaughan; Ahmedullah Aziz (CoRR, 2023)

Roadmap on Neuromorphic Photonics. - Daniel Brunner; Bhavin J. Shastri; Mohammed Al-Qadasi; Hitesh Ballani; Sylvain Barbay; Stefano Biasi; Peter Bienstman; Simon Bilodeau; Wim Bogaerts; Fabian Böhm; Grace Brennan; Sonia M. Buckley; et al. (CoRR, 2025)

Scaling of hardware-compatible perturbative training algorithms. - Bakhrom G. Oripov; Andrew M. Dienstfrey; Adam N. McCaughan; Sonia M. Buckley (CoRR, 2025)