F. Elsner

77.1k total citations
19 papers, 296 citations indexed

About

F. Elsner is a scholar working on Astronomy and Astrophysics, Molecular Biology and Computer Vision and Pattern Recognition. According to data from OpenAlex, F. Elsner has authored 19 papers receiving a total of 296 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Astronomy and Astrophysics, 3 papers in Molecular Biology and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in F. Elsner's work include Cosmology and Gravitation Theories (10 papers), Galaxies: Formation, Evolution, Phenomena (8 papers) and Radio Astronomy Observations and Technology (7 papers). F. Elsner is often cited by papers focused on Cosmology and Gravitation Theories (10 papers), Galaxies: Formation, Evolution, Phenomena (8 papers) and Radio Astronomy Observations and Technology (7 papers). F. Elsner collaborates with scholars based in United States, Germany and France. F. Elsner's co-authors include B. D. Wandelt, Hiranya V. Peiris, Boris Leistedt, A. Mangilli, Wolfgang Kern, Torsten Haferlach, Alexander Höllein, Peter Krawitz, Richard Schabath and Claudia Haferlach and has published in prestigious journals such as Blood, The Astrophysical Journal and Monthly Notices of the Royal Astronomical Society.

In The Last Decade

F. Elsner

18 papers receiving 291 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
F. Elsner United States 10 190 63 45 38 36 19 296
J. Fergusson United Kingdom 15 608 3.2× 319 5.1× 15 0.3× 13 0.3× 27 0.8× 28 756
Hossein Safari Iran 13 334 1.8× 23 0.4× 88 2.0× 41 1.1× 64 1.8× 45 442
C. S. Carvalho Portugal 10 310 1.6× 220 3.5× 12 0.3× 5 0.1× 19 0.5× 28 396
P. L. Bornmann United States 10 368 1.9× 26 0.4× 54 1.2× 9 0.2× 30 0.8× 22 389
Karl Johan Donner Finland 11 230 1.2× 32 0.5× 16 0.4× 8 0.2× 43 1.2× 23 296
Marcelo B. Ribeiro Brazil 14 297 1.6× 122 1.9× 20 0.4× 3 0.1× 16 0.4× 37 547
J. Davies United Kingdom 10 413 2.2× 88 1.4× 11 0.2× 20 0.5× 49 1.4× 19 532
Il‐Hyun Cho South Korea 13 520 2.7× 15 0.2× 91 2.0× 23 0.6× 130 3.6× 34 584
N. A. Walton United Kingdom 17 576 3.0× 65 1.0× 65 1.4× 11 0.3× 29 0.8× 82 736

Countries citing papers authored by F. Elsner

Since Specialization
Citations

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

Fields of papers citing papers by F. Elsner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of F. Elsner

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

All Works

19 of 19 papers shown
1.
Meintker, Lisa, Alexander Höllein, F. Elsner, et al.. (2021). Knowledge transfer to enhance the performance of deep learning models for automated classification of B cell neoplasms. Patterns. 2(10). 100351–100351. 18 indexed citations
2.
Höllein, Alexander, Richard Schabath, Claudia Haferlach, et al.. (2020). Hematologist‐Level Classification of Mature B‐Cell Neoplasm Using Deep Learning on Multiparameter Flow Cytometry Data. Cytometry Part A. 97(10). 1073–1080. 44 indexed citations
3.
Elsner, F., Richard Schabath, Claudia Haferlach, et al.. (2019). Knowledge Transfer between Artificial Neural Networks for Different Multicolor Flow Cytometry Protocols Improves Classification Performance for Rare B-Cell Neoplasm Subtypes. Blood. 134(Supplement_1). 2094–2094. 2 indexed citations
4.
Kern, Wolfgang, F. Elsner, Richard Schabath, et al.. (2019). An Artificial Neural Network Providing Highly Reliable Decision Support in a Routine Setting for Classification of B-Cell Neoplasms Based on Flow Cytometric Raw Data. Blood. 134(Supplement_1). 886–886. 3 indexed citations
5.
Elsner, F., Boris Leistedt, & Hiranya V. Peiris. (2016). Unbiased pseudo-Cℓpower spectrum estimation with mode projection. Monthly Notices of the Royal Astronomical Society. 465(2). 1847–1855. 22 indexed citations
6.
Elsner, F., Boris Leistedt, & Hiranya V. Peiris. (2015). Unbiased methods for removing systematics from galaxy clustering measurements. Monthly Notices of the Royal Astronomical Society. 456(2). 2095–2104. 21 indexed citations
7.
Feeney, Stephen M., F. Elsner, Matthew C. Johnson, & Hiranya V. Peiris. (2015). Forecasting constraints from the cosmic microwave background on eternal inflation. Physical review. D. Particles, fields, gravitation, and cosmology. 92(8).
8.
Benabed, K., F. R. Bouchet, J.-F. Cardoso, et al.. (2014). CMB polarization can constrain cosmology better than CMB temperature. Physical review. D. Particles, fields, gravitation, and cosmology. 90(6). 39 indexed citations
9.
Elsner, F. & B. D. Wandelt. (2013). Efficient Wiener filtering without preconditioning. Springer Link (Chiba Institute of Technology). 46 indexed citations
10.
Mangilli, A., B. D. Wandelt, F. Elsner, & M. Liguori. (2013). Optimal bispectrum estimator and simulations of the CMB lensing-integrated Sachs Wolfe non-Gaussian signal. Astronomy and Astrophysics. 555. A82–A82. 6 indexed citations
11.
Elsner, F. & B. D. Wandelt. (2013). Compressed convolution. Astronomy and Astrophysics. 561. A88–A88. 1 indexed citations
12.
Elsner, F. & B. D. Wandelt. (2012). Fast calculation of the Fisher matrix for cosmic microwave background experiments. Springer Link (Chiba Institute of Technology). 9 indexed citations
13.
Elsner, F. & B. D. Wandelt. (2012). Likelihood, Fisher information, and systematics of cosmic microwave background experiments. Astronomy and Astrophysics. 542. A60–A60. 7 indexed citations
14.
Elsner, F., B. D. Wandelt, & M. Schneider. (2010). Probing local non-Gaussianities within a Bayesian framework. Springer Link (Chiba Institute of Technology). 7 indexed citations
15.
Elsner, F. & B. D. Wandelt. (2010). LOCAL NON-GAUSSIANITY IN THE COSMIC MICROWAVE BACKGROUND THE BAYESIAN WAY. The Astrophysical Journal. 724(2). 1262–1269. 14 indexed citations
16.
Banday, A. J., et al.. (2010). The primordial non-Gaussianity of local type (flocalNL) in the WMAP 5-year data: the length distribution of CMB skeleton. Monthly Notices of the Royal Astronomical Society. 407(4). 2141–2156. 2 indexed citations
17.
Borasio, Gian Domenico, A Kopf, Friedemann Nauck, et al.. (2010). Palliativmedizinische Lehre in Deutschland – Bestandsaufnahme an den medizinischen Fakultäten 2010. Zeitschrift für Palliativmedizin. 11(5). 6 indexed citations
18.
Elsner, F. & B. D. Wandelt. (2009). IMPROVED SIMULATION OF NON-GAUSSIAN TEMPERATURE AND POLARIZATION COSMIC MICROWAVE BACKGROUND MAPS. The Astrophysical Journal Supplement Series. 184(2). 264–270. 38 indexed citations
19.
Elsner, F., et al.. (1989). A dye ring-laser spectrometer for precision spectroscopy. Applied Physics B. 49(3). 251–256. 11 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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