Elies Gil-Fuster

494 total citations · 1 hit paper
6 papers, 272 citations indexed

About

Elies Gil-Fuster is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics and Computational Theory and Mathematics. According to data from OpenAlex, Elies Gil-Fuster has authored 6 papers receiving a total of 272 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 2 papers in Atomic and Molecular Physics, and Optics and 1 paper in Computational Theory and Mathematics. Recurrent topics in Elies Gil-Fuster's work include Quantum Computing Algorithms and Architecture (6 papers), Quantum Information and Cryptography (5 papers) and Machine Learning and Algorithms (1 paper). Elies Gil-Fuster is often cited by papers focused on Quantum Computing Algorithms and Architecture (6 papers), Quantum Information and Cryptography (5 papers) and Machine Learning and Algorithms (1 paper). Elies Gil-Fuster collaborates with scholars based in Germany, Netherlands and Denmark. Elies Gil-Fuster's co-authors include Jens Eisert, Johannes Jakob Meyer, Francesco Arzani, Antonio Anna Mele, C. Matthias, Ryan Sweke, David Wierichs, Carlos Bravo-Prieto, Vedran Dunjko and Sofiène Jerbi and has published in prestigious journals such as Nature Communications, Physical review. A and PRX Quantum.

In The Last Decade

Elies Gil-Fuster

6 papers receiving 259 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Exploiting Symmetry in Variational Quantum Machine Learning

2023 101 citations Johannes Jakob Meyer, Elies Gil-Fuster et al. PRX Quantum profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Elies Gil-Fuster Germany	5	244	87	43	16	16	6	272
Bobak T. Kiani United States	7	231 0.9×	91 1.0×	50 1.2×	11 0.7×	16 1.0×	15	251
Sofiène Jerbi Austria	6	255 1.0×	71 0.8×	34 0.8×	13 0.8×	35 2.2×	11	289
Pierre-Luc Dallaire-Demers Germany	6	356 1.5×	126 1.4×	55 1.3×	16 1.0×	49 3.1×	6	389
Ophelia Crawford United Kingdom	6	213 0.9×	137 1.6×	60 1.4×	13 0.8×	29 1.8×	11	264
Marshall Drew-Brook Canada	3	209 0.9×	73 0.8×	72 1.7×	24 1.5×	23 1.4×	3	254
Narendra N. Hegade Spain	6	170 0.7×	90 1.0×	38 0.9×	12 0.8×	13 0.8×	15	218
Dawei Lu China	6	232 1.0×	165 1.9×	41 1.0×	20 1.3×	12 0.8×	7	265
Ewin Tang United States	9	174 0.7×	93 1.1×	42 1.0×	7 0.4×	11 0.7×	14	216
Changpeng Shao United Kingdom	9	204 0.8×	71 0.8×	60 1.4×	10 0.6×	19 1.2×	24	242
Zhikuan Zhao Switzerland	8	276 1.1×	96 1.1×	99 2.3×	6 0.4×	20 1.3×	11	301

Countries citing papers authored by Elies Gil-Fuster

Since Specialization

Citations

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

Fields of papers citing papers by Elies Gil-Fuster

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Elies Gil-Fuster. 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 Elies Gil-Fuster. The network helps show where Elies Gil-Fuster may publish in the future.

Co-authorship network of co-authors of Elies Gil-Fuster

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

All Works

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6 of 6 papers shown

1.

Sweke, Ryan, et al.. (2025). Potential and limitations of random Fourier features for dequantizing quantum machine learning. Quantum. 9. 1640–1640. 4 indexed citations

2.

Gil-Fuster, Elies, Jens Eisert, & Vedran Dunjko. (2024). On the expressivity of embedding quantum kernels. Machine Learning Science and Technology. 5(2). 25003–25003. 8 indexed citations

3.

Gil-Fuster, Elies, Jens Eisert, & Carlos Bravo-Prieto. (2024). Understanding quantum machine learning also requires rethinking generalization. Nature Communications. 15(1). 2277–2277. 28 indexed citations

4.

Meyer, Johannes Jakob, et al.. (2023). Exploiting Symmetry in Variational Quantum Machine Learning. PRX Quantum. 4(1). 101 indexed citations breakdown →

5.

Wierichs, David, et al.. (2022). Training quantum embedding kernels on near-term quantum computers. Physical review. A. 106(4). 67 indexed citations

6.

Matthias, C., Elies Gil-Fuster, Johannes Jakob Meyer, Jens Eisert, & Ryan Sweke. (2021). Encoding-dependent generalization bounds for parametrized quantum circuits. arXiv (Cornell University). 64 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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