Qianxiao Li

53 papers receiving 1.2k citations

Hit Papers

Extended dynamic mode decomposition with dictionary learn...20172026202020232017202350100150200

Peers

Qianxiao Li
Comparison fields: 5 of 127
  • Materials Chemistry 448
  • Statistical and Nonlinear Physics 299
  • Artificial Intelligence 185
  • Electrical and Electronic Engineering 177
  • Biomedical Engineering 176
Replace Michael R. von Spakovsky with:
Michael R. von Spakovsky United States
Xiu Yang United States
Dong Ni China
Francesco Ferranti Belgium
Maria Longobardi Italy
Joel A. Paulson United States
Kaiwen Zhou China
Lin Xiao China
Huan Su China
Qianxiao Li relative to Michael R. von Spakovsky United States Michael R. von Spakovsky's profile →
Citations per field
00.5×2.5×
Michael R. von Spakovsky · 1×
Citations per year

Countries citing papers authored by Qianxiao Li

Since Specialization
Citations

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

Fields of papers citing papers by Qianxiao Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qianxiao Li

This figure shows the co-authorship network connecting the top 25 collaborators of Qianxiao Li. A scholar is included among the top collaborators of Qianxiao Li 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 Qianxiao Li. Qianxiao Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 3
3 1
4 34
5 2
6 6
7 20
8 2
9 8
10 7
11 6
12 174
13
Towards Robust Neural Networks via Close-loop Control
4
14 34
15 28
16 1
17
A Mean-Field Optimal Control Formulation of Deep Learning
1
18
An Optimal Control Approach to Deep Learning and Applications to Discrete-Weight Neural Networks
4
19
An Equal Space for Complex Data with Unknown Internal Order: Observability, Gauge Invariance and Manifold Learning
1
20 22

About Qianxiao Li

Qianxiao Li is a scholar working on Statistical and Nonlinear Physics, Modeling and Simulation and Artificial Intelligence, having authored 56 papers that have together received 1.2k indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (18 papers), Machine Learning in Materials Science (10 papers) and Neural Networks and Applications (8 papers). The work is most often cited by research in Statistical and Nonlinear Physics (299 citations), Statistics, Probability and Uncertainty (87 citations) and Materials Chemistry (448 citations). Qianxiao Li has collaborated with scholars based in Singapore, United States and China. Frequent co-authors include Felix Dietrich, Ioannis G. Kevrekidis, Erik M. Bollt, Tonio Buonassisi, Kedar Hippalgaonkar, Xiaonan Wang, Jatin Kumar, Jun Ye, Zekun Ren and E Weinan. Their work appears in journals such as Proceedings of the National Academy of Sciences, Advanced Functional Materials and Journal of Computational Physics.

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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