Chao Ma
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 2%
- Information Systems top 5%
- Electrical and Electronic Engineering
- Computer Networks and Communications top 5%
- Topics
- Topic Modeling (13 papers)Machine Learning and ELM (10 papers)Service-Oriented Architecture and Web Services (9 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceApplied EnergyExpert Systems with Applications
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Chao Ma
112 papers receiving 2.2k citations
Hit Papers
Peers
Comparison fields: 5 of 160
- Artificial Intelligence 988
- Computer Vision and Pattern Recognition 431
- Information Systems 258
- Electrical and Electronic Engineering 207
- Computer Networks and Communications 176
Countries citing papers authored by Chao Ma
This map shows the geographic impact of Chao Ma'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 Chao Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chao Ma more than expected).
Fields of papers citing papers by Chao Ma
This network shows the impact of papers produced by Chao Ma. 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 Chao Ma. The network helps show where Chao Ma may publish in the future.
Co-authorship network of co-authors of Chao Ma
This figure shows the co-authorship network connecting the top 25 collaborators of Chao Ma. A scholar is included among the top collaborators of Chao Ma based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Chao Ma. Chao Ma is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 3 | |
| 3 | 32 | |
| 4 | Explainable artificial intelligence for digital finance and consumption upgradingbreakdown → | 146 |
| 5 | 1 | |
| 6 | 49 | |
| 7 | 1 | |
| 8 | 5 | |
| 9 | 39 | |
| 10 | 8 | |
| 11 | 30 | |
| 12 | 69 | |
| 13 | Barron Spaces and the Compositional Function Spaces for Neural Network Models. | 27 |
| 14 | Electricity Price Cross Subsidy Calculation Model Considering Load Characteristics of Electricity Consumers | 2 |
| 15 | 91 | |
| 16 | How SGD Selects the Global Minima in Over-parameterized Learning: A Dynamical Stability Perspective | 26 |
| 17 | Joint Neural Entity Disambiguation with Output Space Search | 1 |
| 18 | Select-and-Evaluate: A Learning Framework for Large-Scale Knowledge Graph Search | 6 |
| 19 | Multi-Task Structured Prediction for Entity Analysis: Search-Based Learning Algorithms | 2 |
| 20 | Application of Neural Network and IP Marking in DDoS Attack Defence | 2 |
About Chao Ma
Chao Ma is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems, having authored 123 papers that have together received 2.2k indexed citations. Recurring topics across this work include Topic Modeling (13 papers), Machine Learning and ELM (10 papers) and Service-Oriented Architecture and Web Services (9 papers). The work is most often cited by research in Artificial Intelligence (988 citations), Computer Vision and Pattern Recognition (431 citations) and Media Technology (106 citations). Chao Ma has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Huiling Chen, Xuehua Zhao, Xiaochuan Shi, Wei Li, Daoliang Li, Bo Yang, Yungang Zhu, Wenbin Liu, Gang Wang and Sujing Wang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Applied Energy and Expert Systems with Applications.
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.