Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Daokun Zhang"'
Publikováno v:
ISPRS Journal of Photogrammetry and Remote Sensing. 196:134-145
We present the hierarchical graph infomax (HGI) approach for learning urban region representations (vector embeddings) with points-of-interest (POIs) in a fully unsupervised manner, which can be used in various downstream tasks. Specifically, HGI com
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::079e00fb4abe26dcdf730322a133555d
https://doi.org/10.1016/j.isprsjprs.2022.11.021
https://doi.org/10.1016/j.isprsjprs.2022.11.021
Autor:
Anh T. N. Nguyen, Diep T. N. Nguyen, Huan Yee Koh, Jason Toskov, William MacLean, Andrew Xu, Daokun Zhang, Geoffrey I. Webb, Lauren T. May, Michelle L. Halls
Publikováno v:
British Journal of Pharmacology.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5020508e7d28346007d3ff3f945e2179
https://doi.org/10.1111/bph.16140
https://doi.org/10.1111/bph.16140
Publikováno v:
International Journal of Geographical Information Science. 36:1905-1930
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::adf6900d9e21ba245cdcf1f5a470ee9e
https://doi.org/10.1080/13658816.2022.2040510
https://doi.org/10.1080/13658816.2022.2040510
Autor:
Zhikang Wang, Qian Gao, Xiao-Ping Yi, Xinyu Zhang, Yiwen Zhang, Daokun Zhang, Pietro Liò, Christopher Bain, Richard Bassed, Shanshan Li, Yuming Guo, Seiya Imoto, Jianhua Yao, Roger J. Daly, Jiangning Song
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9ee5b33cd723e28d87e2df60dca7971b
https://doi.org/10.2139/ssrn.4423682
https://doi.org/10.2139/ssrn.4423682
Autor:
Kai Zhang, Daokun Zhang, Ning Liu, Yonghua Yang, Yonghui Xu, Zhongmin Yan, Hui Li, Lizhen Cui
Publikováno v:
Database Systems for Advanced Applications ISBN: 9783031306716
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ad04e5f26b047ef5ec40020d99f3b498
https://doi.org/10.1007/978-3-031-30672-3_54
https://doi.org/10.1007/978-3-031-30672-3_54
Publikováno v:
Computational Materials Science. 222:112119
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f29b481245426e015708d8905898ab01
https://doi.org/10.1016/j.commatsci.2023.112119
https://doi.org/10.1016/j.commatsci.2023.112119
Publikováno v:
IEEE Transactions on Big Data. 6:3-28
With the widespread use of information technologies, information networks are becoming increasingly popular to capture complex relationships across various disciplines, such as social networks, citation networks, telecommunication networks, and biolo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::98246d4878a5c1ce192a0154fbd8f30c
https://doi.org/10.1109/tbdata.2018.2850013
https://doi.org/10.1109/tbdata.2018.2850013
Link prediction aims to infer the link existence between pairs of nodes in networks/graphs. Despite their wide application, the success of traditional link prediction algorithms is hindered by three major challenges -- link sparsity, node attribute n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::35be8931b4fd8a15d749e0706d7aff7f
http://arxiv.org/abs/2201.10069
http://arxiv.org/abs/2201.10069
Publikováno v:
IEEE Transactions on Circuits and Systems for Video Technology. :1-1
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4cc00dd17c4b0ee52d35e1e18d86534e
https://doi.org/10.1109/tcsvt.2023.3264717
https://doi.org/10.1109/tcsvt.2023.3264717
Publikováno v:
Data Mining and Knowledge Discovery. 33:1953-1980
Network embedding aims to learn a latent, low-dimensional vector representations of network nodes, effective in supporting various network analytic tasks. While prior arts on network embedding focus primarily on preserving network topology structure
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::39b3c71a95e7ee10228228b5243a21ec
https://doi.org/10.1007/s10618-019-00650-2
https://doi.org/10.1007/s10618-019-00650-2