Wenlong Mou
About
In The Last Decade
Wenlong Mou
14 papers receiving 134 citations
Peers
Comparison fields: 5 of 45
- Artificial Intelligence 104
- Electrical and Electronic Engineering 22
- Statistics and Probability 18
- Computer Science Applications 18
- Computer Networks and Communications 12
Countries citing papers authored by Wenlong Mou
This map shows the geographic impact of Wenlong Mou'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 Wenlong Mou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wenlong Mou more than expected).
Fields of papers citing papers by Wenlong Mou
This network shows the impact of papers produced by Wenlong Mou. 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 Wenlong Mou. The network helps show where Wenlong Mou may publish in the future.
Co-authorship network of co-authors of Wenlong Mou
This figure shows the co-authorship network connecting the top 25 collaborators of Wenlong Mou. A scholar is included among the top collaborators of Wenlong Mou 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 Wenlong Mou. Wenlong Mou 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 | 1 | |
| 3 | 7 | |
| 4 | 1 | |
| 5 | High-Order Langevin Diffusion Yields an Accelerated MCMC Algorithm | 15 |
| 6 | 5 | |
| 7 | On Linear Stochastic Approximation: Fine-grained Polyak-Ruppert and Non-Asymptotic Concentration | 3 |
| 8 | 3 | |
| 9 | 9 | |
| 10 | Dropout Training, Data-dependent Regularization, and Generalization Bounds | 9 |
| 11 | Differentially Private Clustering in High-Dimensional Euclidean Spaces | 24 |
| 12 | Generalization Bounds of SGLD for Non-convex Learning: Two Theoretical Viewpoints | 4 |
| 13 | Collect at Once, Use Effectively: Making Non-interactive Locally Private Learning Possible | 2 |
| 14 | 54 | |
| 15 | 1 |
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.