Larry Wasserman
- Artificial Intelligence top 10%
- Statistics and Probability top 5%
- Molecular Biology
- Astronomy and Astrophysics
- Computer Networks and Communications
- Co-authors
- Christopher R. GenoveseR. C. NicholPeter E. FreemanCharles MillerP. J. ShelusD. StoryMarco Perone-PacificoAlessandro Rinaldo
- Topics
- Astro and Planetary Science (2 papers)Ionosphere and magnetosphere dynamics (1 paper)Cosmology and Gravitation Theories (1 paper)
- Journals
- Journal of the American Statistical AssociationThe Astrophysical JournalarXiv (Cornell University)
- Partner nations
- United KingdomUnited States
In The Last Decade
Larry Wasserman
11 papers receiving 518 citations
Hit Papers
Peers
Comparison fields: 5 of 147
- Artificial Intelligence 131
- Statistics and Probability 62
- Molecular Biology 47
- Astronomy and Astrophysics 45
- Computer Networks and Communications 44
Countries citing papers authored by Larry Wasserman
This map shows the geographic impact of Larry Wasserman'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 Larry Wasserman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Larry Wasserman more than expected).
Fields of papers citing papers by Larry Wasserman
This network shows the impact of papers produced by Larry Wasserman. 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 Larry Wasserman. The network helps show where Larry Wasserman may publish in the future.
Co-authorship network of co-authors of Larry Wasserman
This figure shows the co-authorship network connecting the top 25 collaborators of Larry Wasserman. A scholar is included among the top collaborators of Larry Wasserman 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 Larry Wasserman. Larry Wasserman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Statistical Inference For Persistent Homology: Confidence Sets For Persistence Diagrams | 3 |
| 2 | All of Statistics: A Concise Course in Statistical Inferencebreakdown → | 498 |
| 3 | Nonparametric Filament Estimation | 5 |
| 4 | Tree Density Estimation | 4 |
| 5 | Results from the 2009 April 21 Pluto Occultation | 1 |
| 6 | 24 | |
| 7 | Multi-Tree Methods for Statistics on Very Large Datasets in Astronomy | 1 |
| 8 | 6 | |
| 9 | The Distance to the Hyades Cluster Based on HST FGS3 Parallaxes | 2 |
| 10 | CCD Camera Occultation System | 4 |
| 11 | 7 |
About Larry Wasserman
Larry Wasserman is a scholar working on Astronomy and Astrophysics, Biophysics and Environmental Engineering, having authored 11 papers that have together received 555 indexed citations. Recurring topics across this work include Astro and Planetary Science (2 papers), Ionosphere and magnetosphere dynamics (1 paper) and Cosmology and Gravitation Theories (1 paper). The work is most often cited by research in Statistics and Probability (62 citations), Artificial Intelligence (131 citations) and Signal Processing (38 citations). Larry Wasserman has collaborated with scholars based in United Kingdom and United States. Frequent co-authors include Christopher R. Genovese, R. C. Nichol, Peter E. Freeman, Charles Miller, P. J. Shelus, D. Story, Marco Perone-Pacifico, Alessandro Rinaldo, Sivaraman Balakrishnan and O. G. Franz. Their work appears in journals such as Journal of the American Statistical Association, The Astrophysical Journal and arXiv (Cornell University).
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.