Opportunities for neuromorphic computing algorithms and applications

By Catherine D. Schuman, Shruti R. Kulkarni, Maryam Parsa, J. Parker Mitchell, Prasanna Date, Bill Kay. Nature Computational Science, 2022

1,018 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/293d1f2fe3c47b8a4934dbc9ee45cb6df66a4c75

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Guoqi Li
2. Liuliang Yuan
3. Yonghong Tian

In Electrical and Electronic Engineering

1. Yonghong Tian
2. Liuliang Yuan
3. Man Yao
4. Boxing Xu
5. Zhaokun Zhou
6. Jiakui Hu
7. Guoqi Li

Citations in the corpus

• Spike-driven Transformer (2023, methodology): “Bio-inspired Spiking Neural Networks can profit from advanced deep learning and neuroscience knowledge concurrently [28, 5, 7, 29].”