Multilevel phase-change memory
Nikolaos Papandreou, Angeliki Pantazi, et al.
ICECS 2010
Deep learning has achieved outstanding success in several artificial intelligence (AI) tasks, resulting in human-like performance, albeit at a much higher power than the ~20 watts required by the human brain. We have developed an approach that incorporates biologically inspired neural dynamics into deep learning using a novel construct called spiking neural unit (SNU). Remarkably, these biological insights enabled SNU-based deep learning to even surpass the state-of-the-art performance while simultaneously enhancing the energy-efficiency of AI hardware implementations.
Nikolaos Papandreou, Angeliki Pantazi, et al.
ICECS 2010
Olivier Maher, N. Harnack, et al.
DRC 2023
Yiming Chen, Niharika DSouza, et al.
MICCAI 2024
Lukas Heuberger, Daniel Messmer, et al.
Advanced Science