Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Bizhao Shi"'
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-15 (2024)
Abstract Processing spatiotemporal data sources with both high spatial dimension and rich temporal information is a ubiquitous need in machine intelligence. Recurrent neural networks in the machine learning domain and bio-inspired spiking neural netw
Externí odkaz:
https://doaj.org/article/74179e5e820f407c9a457a951cfd838f
Publikováno v:
Proceedings of the 2023 ACM/SIGDA International Symposium on Field Programmable Gate Arrays.
Publikováno v:
Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design.
Publikováno v:
2022 27th Asia and South Pacific Design Automation Conference (ASP-DAC).
Autor:
Bizhao Shi, Jiaxi Zhang, Zhuolun He, Xuechao Wei, Sicheng Li, Guojie Luo, Hongzhong Zheng, Yuan Xie
Publikováno v:
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. :1-1
Publikováno v:
DAC
In recent years, Graph Neural Networks (GNNs) appear to be state-of-the-art algorithms for analyzing non-euclidean graph data. By applying deep-learning to extract high-level representations from graph structures, GNNs achieve extraordinary accuracy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ffe2e92a7fbd3cf18a940db01539999f
Publikováno v:
FPT
With the rapid development of computer vision theory and visual display devices, High Frame Rate (HFR) and Ultra High Definition (UHD) techniques have received increasing attention from academic and industry. As they put high demands on performance a