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
Leo Gross, Fabian Paschke, et al.
DPG Spring Meeting 2025
Jianke Yang, Wang Rao, et al.
NeurIPS 2024
Takuya Kurihana, Kyongmin Yeo, et al.
AGU Fall 2023