Juan Pavez

730 total citations
14 papers, 314 citations indexed

About

Juan Pavez is a scholar working on Artificial Intelligence, Nuclear and High Energy Physics and Electrical and Electronic Engineering. According to data from OpenAlex, Juan Pavez has authored 14 papers receiving a total of 314 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 5 papers in Nuclear and High Energy Physics and 2 papers in Electrical and Electronic Engineering. Recurrent topics in Juan Pavez's work include Particle physics theoretical and experimental studies (5 papers), High-Energy Particle Collisions Research (5 papers) and Particle Detector Development and Performance (5 papers). Juan Pavez is often cited by papers focused on Particle physics theoretical and experimental studies (5 papers), High-Energy Particle Collisions Research (5 papers) and Particle Detector Development and Performance (5 papers). Juan Pavez collaborates with scholars based in Chile, United States and Belgium. Juan Pavez's co-authors include Gilles Louppe, Johann Brehmer, K. Cranmer, Kyle Cranmer, Héctor Allende, José Rodríguez, J. Pontt, Héctor Allende‐Cid, Felix Kling and A. Held and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and SHILAP Revista de lepidopterología.

In The Last Decade

Juan Pavez

14 papers receiving 309 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Juan Pavez Chile	7	187	118	36	26	22	14	314
Johann Brehmer United States	12	454 2.4×	149 1.3×	30 0.8×	100 3.8×	24 1.1×	23	600
Alexey Svyatkovskiy United States	5	136 0.7×	68 0.6×	27 0.8×	25 1.0×	10 0.5×	8	279
Julian Kates‐Harbeck United States	5	138 0.7×	57 0.5×	29 0.8×	27 1.0×	9 0.4×	10	303
Philip Harris United States	9	226 1.2×	106 0.9×	28 0.8×	39 1.5×	40 1.8×	21	357
Frank Gaede Germany	12	428 2.3×	99 0.8×	45 1.3×	21 0.8×	45 2.0×	39	526
I. Kisel Germany	9	238 1.3×	51 0.4×	15 0.4×	9 0.3×	11 0.5×	61	328
Sascha Diefenbacher Germany	10	252 1.3×	90 0.8×	12 0.3×	22 0.8×	39 1.8×	16	320
Philip Waite United Kingdom	6	149 0.8×	66 0.6×	43 1.2×	20 0.8×	4 0.2×	10	256
K. Krüger Germany	10	204 1.1×	102 0.9×	15 0.4×	14 0.5×	46 2.1×	14	390
Kevin Montes United States	9	272 1.5×	92 0.8×	18 0.5×	57 2.2×	8 0.4×	11	378

Countries citing papers authored by Juan Pavez

Since Specialization

Citations

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

Fields of papers citing papers by Juan Pavez

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Juan Pavez

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

All Works

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14 of 14 papers shown

Pavez, Juan & Héctor Allende. (2024). A Hybrid System Based on Bayesian Networks and Deep Learning for Explainable Mental Health Diagnosis. Applied Sciences. 14(18). 8283–8283. 6 indexed citations

Brehmer, Johann, Gilles Louppe, Juan Pavez, & K. Cranmer. (2020). Mining gold from implicit models to improve likelihood-free inference. Proceedings of the National Academy of Sciences. 117(10). 5242–5249. 76 indexed citations

Brehmer, Johann, K. Cranmer, A. Held, et al.. (2020). Constraining effective field theories with machine learning. SHILAP Revista de lepidopterología. 245. 6026–6026. 4 indexed citations

Brehmer, Johann, et al.. (2020). Effective LHC measurements with matrix elements and machine learning. Journal of Physics Conference Series. 1525(1). 12022–12022. 9 indexed citations

Fuentes, Eduardo R., et al.. (2020). WriteWise: software that guides scientific writing. Dialnet (Universidad de la Rioja). 332–333. 1 indexed citations

Brehmer, Johann, et al.. (2019). Effective LHC measurements with matrix elements and machine learning. Open Repository and Bibliography (University of Liège). 1 indexed citations

Brehmer, Johann, Kyle Cranmer, Gilles Louppe, & Juan Pavez. (2018). Constraining Effective Field Theories with Machine Learning. Physical Review Letters. 121(11). 111801–111801. 92 indexed citations

Brehmer, Johann, K. Cranmer, Gilles Louppe, & Juan Pavez. (2018). A guide to constraining effective field theories with machine learning. Physical review. D. 98(5). 88 indexed citations

Pavez, Juan, Héctor Allende, & Héctor Allende‐Cid. (2018). Working Memory Networks: Augmenting Memory Networks with a Relational Reasoning Module. 1000–1009. 8 indexed citations

10.

Pavez, Juan, et al.. (2016). Covariate shift method using approximated density ratios. 5 (6 .)–5 (6 .). 1 indexed citations

11.

Cranmer, K., Juan Pavez, Gilles Louppe, & W. K. Brooks. (2016). Experiments using machine learning to approximate likelihood ratios for mixture models. Journal of Physics Conference Series. 762. 12034–12034. 2 indexed citations

12.

Louppe, Gilles, K. Cranmer, & Juan Pavez. (2016). carl: a likelihood-free inference toolbox. The Journal of Open Source Software. 1(1). 11–11. 8 indexed citations

13.

Pontt, J., et al.. (2004). A mitigation method for non-eliminated harmonics of SHEPWM three-level multipulse three-phase active front end converter. 1. 258–263. 6 indexed citations

14.

Pontt, J., et al.. (2003). Mitigation of noneliminated harmonics of SHEPWM three-level multipulse three-phase active front end converters with low switching frequency for meeting standard IEEE-519-92. 2. 531–536. 12 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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