Katja-Sophia Csizi, Adrianna Frackowiak, et al.
Biomicrofluidics
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.
Katja-Sophia Csizi, Adrianna Frackowiak, et al.
Biomicrofluidics
Pietro Tassan, Darius Urbonas, et al.
ICSCE 2024
Vishal Pallagani, Keerthiram Murugesan, et al.
AAAI 2024
Arash Fathi, Joao Lucas de Sousa Almeida, et al.
AGU Fall 2023