2 papers
cond-mat.dis-nn2023★ 1 cited
Physical learning of power-efficient solutions
Menachem Stern, Sam Dillavou, Dinesh Jayaraman +2
As the size and ubiquity of artificial intelligence and computational machine learning (ML) models grow, their energy consumption for training and use is rapidly becoming economica…
cond-mat.dis-nn2021
Physical learning beyond the quasistatic limit
Menachem Stern, Sam Dillavou, Marc Z. Miskin +2
Physical networks, such as biological neural networks, can learn desired functions without a central processor, using local learning rules in space and time to learn in a fully dis…