Elena Sellentin

1.7k total citations
32 papers, 721 citations indexed

About

Elena Sellentin is a scholar working on Astronomy and Astrophysics, Artificial Intelligence and Statistical and Nonlinear Physics. According to data from OpenAlex, Elena Sellentin has authored 32 papers receiving a total of 721 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Astronomy and Astrophysics, 12 papers in Artificial Intelligence and 5 papers in Statistical and Nonlinear Physics. Recurrent topics in Elena Sellentin's work include Cosmology and Gravitation Theories (13 papers), Galaxies: Formation, Evolution, Phenomena (13 papers) and Gaussian Processes and Bayesian Inference (9 papers). Elena Sellentin is often cited by papers focused on Cosmology and Gravitation Theories (13 papers), Galaxies: Formation, Evolution, Phenomena (13 papers) and Gaussian Processes and Bayesian Inference (9 papers). Elena Sellentin collaborates with scholars based in Netherlands, United Kingdom and Switzerland. Elena Sellentin's co-authors include Alan Heavens, Luca Amendola, Ruth Durrer, H. C. Eggers, Steve Kroon, Y. Fantaye, Miguel Quartin, Will J. Percival, Oliver Friedrich and Catherine Heymans and has published in prestigious journals such as Physical Review Letters, SHILAP Revista de lepidopterología and Journal of Computational Physics.

In The Last Decade

Elena Sellentin

32 papers receiving 698 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Elena Sellentin Netherlands 14 644 204 136 90 79 32 721
Pablo Lemos United Kingdom 19 724 1.1× 308 1.5× 105 0.8× 77 0.9× 84 1.1× 33 853
ChangHoon Hahn United States 18 635 1.0× 105 0.5× 254 1.9× 94 1.0× 90 1.1× 43 752
Stephen M. Feeney United Kingdom 15 737 1.1× 289 1.4× 59 0.4× 100 1.1× 64 0.8× 30 865
Tom Charnock France 10 464 0.7× 211 1.0× 72 0.5× 120 1.3× 39 0.5× 15 566
Elena Massara Canada 18 624 1.0× 239 1.2× 154 1.1× 60 0.7× 84 1.1× 27 746
Jens Jasche France 23 1.3k 1.9× 390 1.9× 246 1.8× 184 2.0× 139 1.8× 55 1.4k
Boris Leistedt United Kingdom 16 528 0.8× 126 0.6× 158 1.2× 34 0.4× 27 0.3× 38 656
Yin Li United States 16 808 1.3× 221 1.1× 247 1.8× 83 0.9× 69 0.9× 35 917
Zachary Slepian United States 16 720 1.1× 205 1.0× 203 1.5× 27 0.3× 127 1.6× 38 828
Pia Mukherjee United Kingdom 18 971 1.5× 531 2.6× 48 0.4× 50 0.6× 73 0.9× 30 1.1k

Countries citing papers authored by Elena Sellentin

Since Specialization
Citations

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

Fields of papers citing papers by Elena Sellentin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Elena Sellentin

This figure shows the co-authorship network connecting the top 25 collaborators of Elena Sellentin. A scholar is included among the top collaborators of Elena Sellentin 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 Elena Sellentin. Elena Sellentin 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.
Sellentin, Elena, et al.. (2024). Stage IV baryonic feedback correction for non-Gaussianity inference. Monthly Notices of the Royal Astronomical Society. 536(3). 2064–2071. 1 indexed citations
2.
Amendola, Luca, et al.. (2024). Distribution of Bayes’ factor. Physical review. D. 110(12). 2 indexed citations
3.
Heavens, Alan, et al.. (2023). Extreme data compression for Bayesian model comparison. Journal of Cosmology and Astroparticle Physics. 2023(11). 48–48. 1 indexed citations
4.
Loureiro, A., et al.. (2023). Almanac: Weak Lensing power spectra and map inference on the masked sphere. SHILAP Revista de lepidopterología. 6. 10 indexed citations
5.
Sellentin, Elena, et al.. (2023). Extremely expensive likelihoods: a variational-Bayes solution for precision cosmology. Monthly Notices of the Royal Astronomical Society. 521(1). 1152–1161. 3 indexed citations
6.
Sellentin, Elena, et al.. (2023). Almanac: MCMC-based signal extraction of power spectra and maps on the sphere. SHILAP Revista de lepidopterología. 6. 4 indexed citations
7.
Fujii, Michiko S., et al.. (2022). Impact of bar resonances in the velocity–space distribution of the solar neighbourhood stars in a self-consistentN-body Galactic disc simulation. Monthly Notices of the Royal Astronomical Society. 514(1). 460–469. 5 indexed citations
8.
Sellentin, Elena, et al.. (2022). Identifying the most constraining ice observations to infer molecular binding energies. Monthly Notices of the Royal Astronomical Society. 517(1). 38–46. 3 indexed citations
9.
Sellentin, Elena, et al.. (2022). Differentiable Predictions for Large Scale Structure with SHAMNet. SHILAP Revista de lepidopterología. 5(1). 4 indexed citations
10.
Rossi, Elena M., Robyn E. Sanderson, Elena Sellentin, et al.. (2021). Galactic potential constraints from clustering in action space of combined stellar stream data. Monthly Notices of the Royal Astronomical Society. 502(3). 4170–4193. 31 indexed citations
11.
Ravenni, Andrea, et al.. (2021). Breaking degeneracies with the Sunyaev-Zeldovich full bispectrum. Padua Research Archive (University of Padova). 3 indexed citations
12.
Percival, Will J., Oliver Friedrich, Elena Sellentin, & Alan Heavens. (2021). Matching Bayesian and frequentist coverage probabilities when using an approximate data covariance matrix. arXiv (Cornell University). 42 indexed citations
13.
Fujii, Michiko S., et al.. (2020). Trimodal structure of Hercules stream explained by originating from bar resonances. Monthly Notices of the Royal Astronomical Society. 499(2). 2416–2425. 30 indexed citations
14.
Sellentin, Elena, et al.. (2019). Euclid-era cosmology for everyone: Neural net assisted MCMC sampling for the joint 3x2 likelihood. Monthly Notices of the Royal Astronomical Society. 21 indexed citations
15.
Heavens, Alan, et al.. (2017). No Evidence for Extensions to the Standard Cosmological Model. Physical Review Letters. 119(10). 101301–101301. 111 indexed citations
16.
Sellentin, Elena & Alan Heavens. (2016). Quantifying lost information due to covariance matrix estimation in parameter inference. Monthly Notices of the Royal Astronomical Society. 464(4). 4658–4665. 26 indexed citations
17.
Amendola, Luca & Elena Sellentin. (2016). Optimizing parameter constraints: a new tool for Fisher matrix forecasts. Monthly Notices of the Royal Astronomical Society. 457(2). 1490–1495. 8 indexed citations
18.
Sellentin, Elena & Björn Malte Schäfer. (2015). Non-Gaussian forecasts of weak lensing with and without priors. Monthly Notices of the Royal Astronomical Society. 456(2). 1645–1653. 8 indexed citations
19.
Sellentin, Elena & Alan Heavens. (2015). Parameter inference with estimated covariance matrices. Monthly Notices of the Royal Astronomical Society Letters. 456(1). L132–L136. 149 indexed citations
20.
Sellentin, Elena, Miguel Quartin, & Luca Amendola. (2014). Breaking the spell of Gaussianity: forecasting with higher order Fisher matrices. Monthly Notices of the Royal Astronomical Society. 441(2). 1831–1840. 47 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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