×
验证码:
换一张
Forgotten Password?
Stay signed in
Login With UMPASS
English
|
繁體
Login With UMPASS
Log In
ALL
ORCID
TI
AU
PY
SU
KW
TY
JN
DA
IN
PB
FP
ST
SM
Study Hall
Image search
Paste the image URL
Home
Faculties & Institutes
Scholars
Publications
Subjects
Statistics
News
Search in the results
Faculties & Institutes
Faculty of Scien... [2]
THE STATE KEY LA... [1]
Authors
CHENGZHONG XU [2]
Document Type
Conference paper [2]
Date Issued
2021 [1]
2020 [1]
Language
英語English [2]
Source Publication
Proceedings - In... [1]
Proceedings - In... [1]
Indexed By
CPCI-S [2]
Funding Organization
Funding Project
×
Knowledge Map
UM
Start a Submission
Submissions
Unclaimed
Claimed
Attach Fulltext
Bookmarks
Browse/Search Results:
1-2 of 2
Help
Selected(
0
)
Clear
Items/Page:
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
Sort:
Select
Journal Impact Factor Ascending
Journal Impact Factor Descending
Title Ascending
Title Descending
Author Ascending
Author Descending
Issue Date Ascending
Issue Date Descending
WOS Cited Times Ascending
WOS Cited Times Descending
Submit date Ascending
Submit date Descending
MA-LSTM: A Multi-Attention Based LSTM for Complex Pattern Extraction
Conference paper
Jingjie Guo, Kelang Tian, Kejiang Ye, Cheng-Zhong Xu. MA-LSTM: A Multi-Attention Based LSTM for Complex Pattern Extraction[C], IEEE COMPUTER SOC, 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA:IEEE, 2021, 3605 - 3611.
Authors:
Jingjie Guo
;
Kelang Tian
;
Kejiang Ye
;
Cheng-Zhong Xu
Favorite
|
TC[WOS]:
5
TC[Scopus]:
7
|
Submit date:2021/09/18
Multi-attention
Traffic Prediction
Handwriting Recognition
Language Model
ST-MGAT: Spatial-Temporal Multi-Head Graph Attention Networks for Traffic Forecasting
Conference paper
Tian,Kelang, Guo,Jingjie, Ye,Kejiang, Xu,Cheng Zhong. ST-MGAT: Spatial-Temporal Multi-Head Graph Attention Networks for Traffic Forecasting[C], 2020, 714-721.
Authors:
Tian,Kelang
;
Guo,Jingjie
;
Ye,Kejiang
;
Xu,Cheng Zhong
Favorite
|
TC[WOS]:
8
TC[Scopus]:
10
|
Submit date:2021/03/09
Graph Convolutional Networks
Spatial-temporal Model
Traffic Forecasting