Lechao Xiao
- Artificial Intelligence
- Applied Mathematics top 10%
- Computer Vision and Pattern Recognition
- Mathematical Physics
- Discrete Mathematics and Combinatorics
- Co-authors
- Jeffrey PenningtonXiaochun LiJaehoon LeeRoman NovakJascha Sohl‐DicksteinJiri HronYasaman BahriSamuel S. Schoenholz
- Topics
- Advanced Harmonic Analysis Research (6 papers)Gaussian Processes and Bayesian Inference (5 papers)Nonlinear Partial Differential Equations (3 papers)
- Partner nations
- United StatesUnited KingdomChina
In The Last Decade
Lechao Xiao
12 papers receiving 103 citations
Peers
Comparison fields: 5 of 36
- Artificial Intelligence 59
- Applied Mathematics 37
- Computer Vision and Pattern Recognition 24
- Mathematical Physics 20
- Discrete Mathematics and Combinatorics 11
Countries citing papers authored by Lechao Xiao
This map shows the geographic impact of Lechao Xiao'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 Lechao Xiao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lechao Xiao more than expected).
Fields of papers citing papers by Lechao Xiao
This network shows the impact of papers produced by Lechao Xiao. 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 Lechao Xiao. The network helps show where Lechao Xiao may publish in the future.
Co-authorship network of co-authors of Lechao Xiao
This figure shows the co-authorship network connecting the top 25 collaborators of Lechao Xiao. A scholar is included among the top collaborators of Lechao Xiao 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 Lechao Xiao. Lechao Xiao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | Finite Versus Infinite Neural Networks: an Empirical Study | 5 |
| 3 | Neural Tangents: Fast and Easy Infinite Neural Networks in Python | 9 |
| 4 | 8 | |
| 5 | Disentangling Trainability and Generalization in Deep Learning | 7 |
| 6 | Bayesian Convolutional Neural Networks with Many Channels are Gaussian Processes. | 5 |
| 7 | 37 | |
| 8 | 2 | |
| 9 | 7 | |
| 10 | 2 | |
| 11 | 6 | |
| 12 | 17 | |
| 13 | 8 |
About Lechao Xiao
Lechao Xiao is a scholar working on Applied Mathematics, Mathematical Physics and Artificial Intelligence, having authored 13 papers that have together received 113 indexed citations. Recurring topics across this work include Advanced Harmonic Analysis Research (6 papers), Gaussian Processes and Bayesian Inference (5 papers) and Nonlinear Partial Differential Equations (3 papers). The work is most often cited by research in Computational Mathematics (3 citations), Applied Mathematics (37 citations) and Discrete Mathematics and Combinatorics (11 citations). Lechao Xiao has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Jeffrey Pennington, Xiaochun Li, Jaehoon Lee, Roman Novak, Jascha Sohl‐Dickstein, Jiri Hron, Yasaman Bahri, Samuel S. Schoenholz, Philip T. Gressman and Greg Yang. Their work appears in journals such as Advances in Mathematics, Journal of Functional Analysis and American Journal of Mathematics.
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.