Bing Yu

1.4k citations
9 papers · 848 · 1 hit paper · h-index 4

Impact in

Papers in

Bing Yu

8 papers receiving 812 citations

Bing Yu's Hit Papers

The Deep Ritz Method: A Deep Learning-Based Numerical Algorithm for Solving Variational Problems 2018 · 810 citations
8100+2+5Years since publication250500750

Peers

Bing Yu
Comparison fields: 5 of 75
  • Statistical and Nonlinear Physics 655
  • Statistics, Probability and Uncertainty 119
  • Computational Mechanics 293
  • Numerical Analysis 55
  • Computational Mathematics 6
Replace Hayden Schaeffer with:
Hayden Schaeffer United States
Jens Berg Sweden
Hanwen Wang China
Deep Ray United States
Federico Negri Switzerland
Matthew J. Zahr United States
Kailiang Wu China
Xueyu Zhu United States
Julien Cortial France
Einar M. Rønquist Norway
Bing Yu relative to Hayden Schaeffer United States Hayden Schaeffer's profile →
Citations per field
00.5×1.5×
Hayden Schaeffer · 1×
Citations per year

Countries citing papers authored by Bing Yu

Since Specialization
Citations

This map shows the geographic impact of Bing Yu'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 Bing Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bing Yu more than expected).

Fields of papers citing papers by Bing Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bing Yu. 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 Bing Yu. The network helps show where Bing Yu may publish in the future.

Co-authors

The 25 scholars most cited alongside Bing Yu, 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 Bing Yu Line = papers co-authored together Bing Yu links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1
The Deep Ritz Method: A Deep Learning-Based Numerical Algorithm for Solving Variational Problems
Hit paper breakdown →
2018810
2 201214
3 201211
4 20187
5 20172
6 20182
7 20151
8 20181
9 20250

About Bing Yu

Bing Yu is a scholar working on Instrumentation, Electrical and Electronic Engineering, Ophthalmology, Biomedical Engineering and Environmental Engineering, having authored 9 papers that have together received 848 indexed citations. Recurring topics across this work include Advanced Optical Sensing Technologies (5 papers), Ocular and Laser Science Research (3 papers), Optical Systems and Laser Technology (3 papers), Optical Coherence Tomography Applications (2 papers), Acoustic Wave Resonator Technologies (1 paper), Advanced Fiber Optic Sensors (1 paper), Remote Sensing and Land Use (1 paper) and Remote Sensing and LiDAR Applications (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (655 citations), Statistics, Probability and Uncertainty (119 citations), Computational Mechanics (293 citations), Numerical Analysis (55 citations) and Computational Mathematics (6 citations). Bing Yu has collaborated with scholars based in China and United States. Frequent co-authors include E Weinan, Hongru Yang, Lei Wu, Xiaopeng Wang, Chao Chen, Yuan Liang, Gaoping Li, Bin Yang, Guangyu Li and Rui Zhang. Their work appears in journals such as Applied Optics, IEEE Sensors Journal, Communications in Mathematics and Statistics, National Remote Sensing Bulletin and Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.

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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