Hannes Leeb
- Statistics and Probability top 0.5%
- Economics and Econometrics top 5%
- General Economics, Econometrics and Finance top 5%
- Artificial Intelligence top 10%
- Finance top 10%
- Co-authors
- Benedikt M. PötscherPaul KabailaStefan WegenkittlAlois LametschwandtnerBernd MinnichPeter HellekalekAdityanand GuntuboyinaYoshiharu Kurita
- Topics
- Statistical Methods and Inference (16 papers)Statistical Methods and Bayesian Inference (9 papers)Advanced Statistical Methods and Models (5 papers)
- Cited by
- Statistics and ProbabilityGeneral Economics, Econometrics and FinanceStatistics, Probability and Uncertainty
- Journals
- Journal of the American Statistical AssociationJournal of EconometricsMathematics of Computation
- Partner nations
- AustriaUnited StatesAustralia
In The Last Decade
Hannes Leeb
27 papers receiving 862 citations
Peers
Comparison fields: 5 of 125
- Statistics and Probability 514
- Economics and Econometrics 208
- General Economics, Econometrics and Finance 139
- Artificial Intelligence 137
- Finance 86
Countries citing papers authored by Hannes Leeb
This map shows the geographic impact of Hannes Leeb'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 Hannes Leeb with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hannes Leeb more than expected).
Fields of papers citing papers by Hannes Leeb
This network shows the impact of papers produced by Hannes Leeb. 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 Hannes Leeb. The network helps show where Hannes Leeb may publish in the future.
Co-authorship network of co-authors of Hannes Leeb
This figure shows the co-authorship network connecting the top 25 collaborators of Hannes Leeb. A scholar is included among the top collaborators of Hannes Leeb 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 Hannes Leeb. Hannes Leeb is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 6 | |
| 3 | Adaptive, Distribution-Free Prediction Intervals for Deep Networks | 7 |
| 4 | 0 | |
| 5 | 7 | |
| 6 | 2 | |
| 7 | 13 | |
| 8 | 82 | |
| 9 | 133 | |
| 10 | 7 | |
| 11 | 44 | |
| 12 | 13 | |
| 13 | 8 | |
| 14 | 2 | |
| 15 | 2 | |
| 16 | 6 | |
| 17 | 48 | |
| 18 | 9 | |
| 19 | 37 | |
| 20 | The Asymptotic Distribution of Diaphony in One Dimension | 1 |
About Hannes Leeb
Hannes Leeb is a scholar working on Statistics and Probability, Discrete Mathematics and Combinatorics and Statistics, Probability and Uncertainty, having authored 29 papers that have together received 900 indexed citations. Recurring topics across this work include Statistical Methods and Inference (16 papers), Statistical Methods and Bayesian Inference (9 papers) and Advanced Statistical Methods and Models (5 papers). The work is most often cited by research in Statistics and Probability (514 citations), General Economics, Econometrics and Finance (139 citations) and Statistics, Probability and Uncertainty (79 citations). Hannes Leeb has collaborated with scholars based in Austria, United States and Australia. Frequent co-authors include Benedikt M. Pötscher, Paul Kabaila, Stefan Wegenkittl, Alois Lametschwandtner, Bernd Minnich, Peter Hellekalek, Adityanand Guntuboyina, Yoshiharu Kurita, Danijel Kivaranovic and Makoto Matsumoto. Their work appears in journals such as Journal of the American Statistical Association, Journal of Econometrics and Mathematics of Computation.
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.