Daling Wang

2.2k citations
141 papers · 1.5k · 1 hit paper · h-index 19

Impact in

Papers in

Daling Wang

125 papers receiving 1.4k citations

Daling Wang's Hit Papers

Is Mamba effective for time series forecasting? 2024 · 113 citations
1130+1Years since publication255075100

Peers

Daling Wang
Comparison fields: 5 of 76
  • Artificial Intelligence 984
  • Computer Vision and Pattern Recognition 175
  • Signal Processing 43
  • Experimental and Cognitive Psychology 81
  • Information Systems 119
Replace Maria Rifqi with:
Maria Rifqi France
Jiuxin Cao China
Zhenguo Yang China
Ilya Makarov Russia
Christophe Marsala France
Xingcheng Yao China
Linmei Hu China
Xiaoliang Chen China
Erheng Zhong Hong Kong
Dawei Zhou United States
Daling Wang relative to Maria Rifqi France Maria Rifqi's profile →
Citations per field
00.5×5×10.6×
Maria Rifqi · 1×
Citations per year

Countries citing papers authored by Daling Wang

Since Specialization
Citations

This map shows the geographic impact of Daling Wang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daling Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daling Wang more than expected).

Fields of papers citing papers by Daling Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daling Wang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daling Wang. The network helps show where Daling Wang may publish in the future.

Co-authors

The 25 scholars most cited alongside Daling Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daling Wang Line = papers co-authored together Daling Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 141 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020191
2
Is Mamba effective for time series forecasting?
Hit paper breakdown →
2024113
3 201895
4 202195
5 201957
6 201841
7 202140
8 201632
9 201030
10 201429
11 201727
12 201622
13 201722
14 201722
15 202122
16 202322
17 201321
18 201821
19 201520
20 201619

About Daling Wang

Daling Wang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Statistical and Nonlinear Physics and Computer Networks and Communications, having authored 141 papers that have together received 1.5k indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (50 papers), Speech and dialogue systems (21 papers), Topic Modeling (11 papers), Advanced Graph Neural Networks (9 papers), Recommender Systems and Techniques (9 papers), Advanced Database Systems and Queries (8 papers), Advanced Clustering Algorithms Research (7 papers) and Complex Network Analysis Techniques (7 papers). The work is most often cited by research in Artificial Intelligence (984 citations), Computer Vision and Pattern Recognition (175 citations), Signal Processing (43 citations), Experimental and Cognitive Psychology (81 citations) and Information Systems (119 citations). Daling Wang has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Shi Feng, Yifei Zhang, Ge Yu, Xiaocui Yang, Kaisong Song, Yifei Zhang, Xiangju Li, Yifei Zhang, Wei Guang Gao and Feng Shi. Their work appears in journals such as Lecture notes in computer science, Knowledge-Based Systems, World Wide Web, Knowledge and Information Systems and Frontiers of Computer Science.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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