Yulong Lu

650 citations
31 papers · 237 · h-index 10

Impact in

Papers in

Yulong Lu

31 papers receiving 227 citations

Peers

Yulong Lu
Comparison fields: 5 of 75
  • Statistical and Nonlinear Physics 81
  • Statistics and Probability 50
  • Mathematical Physics 42
  • Statistics, Probability and Uncertainty 20
  • Applied Mathematics 22
Replace Sui Tang with:
Sui Tang United States
Étienne Tanré France
Karl Friedrich Siburg Germany
Franca Hoffmann United States
Nicola Bruti‐Liberati Australia
Anatoliy Malyarenko Sweden
Sylvain Maire France
Ken Kuriyama Japan
Ludovic Goudenège France
Samuel Taylor United States
Yulong Lu relative to Sui Tang United States Sui Tang's profile →
Citations per field
00.5×2.8×
Sui Tang · 1×
Citations per year

Countries citing papers authored by Yulong Lu

Since Specialization
Citations

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

Fields of papers citing papers by Yulong Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201933
2 201318
3 202016
4 201914
5 202213
6 202313
7 202312
8
A Priori Generalization Analysis of the Deep Ritz Method for Solving High Dimensional Elliptic Partial Differential Equations
202110
9 201710
10 202210
11 20249
12 20178
13 20198
14 20237
15
A Universal Approximation Theorem of Deep Neural Networks for Expressing Distributions.
20206
16 20245
17 20235
18 20185
19 20195
20
A Mean Field Analysis Of Deep ResNet And Beyond: Towards Provably Optimization Via Overparameterization From Depth
20204

About Yulong Lu

Yulong Lu is a scholar working on Statistical and Nonlinear Physics, Mathematical Physics, Statistics and Probability, Artificial Intelligence and Applied Mathematics, having authored 31 papers that have together received 237 indexed citations. Recurring topics across this work include Markov Chains and Monte Carlo Methods (7 papers), Model Reduction and Neural Networks (7 papers), Numerical methods in inverse problems (4 papers), Statistical Mechanics and Entropy (4 papers), Geometric Analysis and Curvature Flows (3 papers), Advanced Thermodynamics and Statistical Mechanics (3 papers), Numerical methods in engineering (3 papers) and Advanced Mathematical Physics Problems (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (81 citations), Statistics and Probability (50 citations), Mathematical Physics (42 citations), Statistics, Probability and Uncertainty (20 citations) and Applied Mathematics (22 citations). Yulong Lu has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Jianfeng Lu, James Nolen, Li Wang, Jonathan C. Mattingly, Andrew M. Stuart, Hendrik Weber, Bo Zhang, Guanghui Hu, Yu Cao and Xiangxiong Zhang. Their work appears in journals such as SIAM Journal on Mathematical Analysis, Nonlinearity, International Journal of Clinical and Experimental Pathology, SIAM Journal on Numerical Analysis and Journal of Coastal Research.

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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