Hannes Leeb

1.8k total citations
29 papers, 900 citations indexed

About

Hannes Leeb is a scholar working on Statistics and Probability, Artificial Intelligence and Statistics, Probability and Uncertainty. According to data from OpenAlex, Hannes Leeb has authored 29 papers receiving a total of 900 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Statistics and Probability, 8 papers in Artificial Intelligence and 4 papers in Statistics, Probability and Uncertainty. Recurrent topics in Hannes Leeb's work include Statistical Methods and Inference (16 papers), Statistical Methods and Bayesian Inference (9 papers) and Advanced Statistical Methods and Models (5 papers). Hannes Leeb is often cited by papers focused on Statistical Methods and Inference (16 papers), Statistical Methods and Bayesian Inference (9 papers) and Advanced Statistical Methods and Models (5 papers). Hannes Leeb collaborates with scholars based in Austria, United States and Australia. Hannes Leeb's 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 and has published in prestigious journals such as Journal of the American Statistical Association, Journal of Econometrics and Mathematics of Computation.

In The Last Decade

Hannes Leeb

27 papers receiving 862 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Hannes Leeb Austria 10 514 208 139 137 86 29 900
Marlene Müller Germany 10 375 0.7× 191 0.9× 51 0.4× 206 1.5× 97 1.1× 17 984
Chunming Zhang United States 14 576 1.1× 114 0.5× 67 0.5× 141 1.0× 219 2.5× 62 947
Raja P. Velu United States 13 287 0.6× 169 0.8× 103 0.7× 95 0.7× 120 1.4× 36 807
Alexander Samarov United States 11 337 0.7× 210 1.0× 56 0.4× 97 0.7× 264 3.1× 15 710
Takeaki Kariya Japan 17 454 0.9× 138 0.7× 43 0.3× 113 0.8× 152 1.8× 68 892
Tatyana Krivobokova Germany 12 319 0.6× 120 0.6× 58 0.4× 100 0.7× 44 0.5× 27 700
Daniel J. Nordman United States 16 261 0.5× 145 0.7× 44 0.3× 150 1.1× 117 1.4× 69 658
Jiancheng Jiang United States 18 535 1.0× 113 0.5× 52 0.4× 153 1.1× 140 1.6× 49 840
Carlos M. Carvalho United States 13 471 0.9× 173 0.8× 57 0.4× 402 2.9× 149 1.7× 41 1.2k
Lan Wang United States 19 1.0k 2.0× 140 0.7× 29 0.2× 337 2.5× 70 0.8× 60 1.5k

Countries citing papers authored by Hannes Leeb

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

20 of 20 papers shown
1.
Kivaranovic, Danijel & Hannes Leeb. (2024). A (tight) upper bound for the length of confidence intervals with conditional coverage. Electronic Journal of Statistics. 18(1). 1 indexed citations
2.
Leeb, Hannes, et al.. (2023). Conditional predictive inference for stable algorithms. The Annals of Statistics. 51(1). 6 indexed citations
3.
Kivaranovic, Danijel, et al.. (2020). Adaptive, Distribution-Free Prediction Intervals for Deep Networks. ePubWU Institutional Repository (Wirtschaftsuniversität Wien). 4346–4356. 7 indexed citations
4.
Leeb, Hannes, et al.. (2019). Prediction when fitting simple models to high-dimensional data. The Annals of Statistics. 47(3).
5.
Leeb, Hannes. (2013). On the conditional distributions of low-dimensional projections from high-dimensional data. The Annals of Statistics. 41(2). 7 indexed citations
6.
Leeb, Hannes, et al.. (2013). Shrinkage Estimators for Prediction Out-of-Sample: Conditional Performance. Communication in Statistics- Theory and Methods. 42(7). 1246–1264. 2 indexed citations
7.
Leeb, Hannes. (2009). Conditional predictive inference post model selection. The Annals of Statistics. 37(5B). 13 indexed citations
8.
Leeb, Hannes & Benedikt M. Pötscher. (2007). CAN ONE ESTIMATE THE UNCONDITIONAL DISTRIBUTION OF POST-MODEL-SELECTION ESTIMATORS?. Econometric Theory. 24(2). 82 indexed citations
9.
Leeb, Hannes & Benedikt M. Pötscher. (2007). Sparse estimators and the oracle property, or the return of Hodges’ estimator. Journal of Econometrics. 142(1). 201–211. 133 indexed citations
10.
Leeb, Hannes & Benedikt M. Pötscher. (2007). GUEST EDITORS' EDITORIAL: RECENT DEVELOPMENTS IN MODEL SELECTION AND RELATED AREAS. Econometric Theory. 24(2). 319–322. 7 indexed citations
11.
Kabaila, Paul & Hannes Leeb. (2006). On the Large-Sample Minimal Coverage Probability of Confidence Intervals After Model Selection. Journal of the American Statistical Association. 101(474). 619–629. 44 indexed citations
12.
Leeb, Hannes. (2004). The distribution of a linear predictor after model selection: conditional finite-sample distributions and asymptotic approximations. Journal of Statistical Planning and Inference. 134(1). 64–89. 13 indexed citations
13.
Leeb, Hannes, et al.. (2003). THE FINITE-SAMPLE DISTRIBUTION OF POST-MODEL-SELECTION ESTIMATORS AND UNIFORM VERSUS NONUNIFORM APPROXIMATIONS. Econometric Theory. 19(1). 8 indexed citations
14.
Leeb, Hannes & Benedikt M. Pötscher. (2001). THE VARIANCE OF AN INTEGRATED PROCESS NEED NOT DIVERGE TO INFINITY, AND RELATED RESULTS ON PARTIAL SUMS OF STATIONARY PROCESSES. Econometric Theory. 17(4). 671–685. 2 indexed citations
15.
Leeb, Hannes, et al.. (1999). The Variance of an Integrated Process Need Not Diverge to Infinity. SSRN Electronic Journal. 2 indexed citations
16.
Leeb, Hannes, et al.. (1999). New primitive $t$-nomials $(t = 3,5)$ over $GF(2)$ whose degreeis a Mersenne exponent. Mathematics of Computation. 69(230). 811–815. 6 indexed citations
17.
18.
Hellekalek, Peter & Hannes Leeb. (1997). Dyadic diaphony. Acta Arithmetica. 80(2). 187–196. 9 indexed citations
19.
Leeb, Hannes & Stefan Wegenkittl. (1997). Inversive and linear congruential pseudorandom number generators in empirical tests. ACM Transactions on Modeling and Computer Simulation. 7(2). 272–286. 37 indexed citations
20.
Leeb, Hannes. (1996). The Asymptotic Distribution of Diaphony in One Dimension. Les Cahiers du GERAD. 1–7. 1 indexed citations

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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