no code implementations • 14 Nov 2021 • Tena Dubček, Daniel Moreno-Garcia, Thomas Haag, Parisa Omidvar, Henrik R. Thomsen, Theodor S. Becker, Lars Gebraad, Christoph Bärlocher, Fredrik Andersson, Sebastian D. Huber, Dirk-Jan van Manen, Luis Guillermo Villanueva, Johan O. A. Robertsson, Marc Serra-Garcia
Mitigating the energy requirements of artificial intelligence requires novel physical substrates for computation.
4 code implementations • ICML 2017 • Li Jing, Yichen Shen, Tena Dubček, John Peurifoy, Scott Skirlo, Yann Lecun, Max Tegmark, Marin Soljačić
Using unitary (instead of general) matrices in artificial neural networks (ANNs) is a promising way to solve the gradient explosion/vanishing problem, as well as to enable ANNs to learn long-term correlations in the data.