M. Pettee

8.0k total citations
6 papers, 101 citations indexed

About

M. Pettee is a scholar working on Nuclear and High Energy Physics, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, M. Pettee has authored 6 papers receiving a total of 101 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Nuclear and High Energy Physics, 2 papers in Computer Vision and Pattern Recognition and 2 papers in Artificial Intelligence. Recurrent topics in M. Pettee's work include Particle physics theoretical and experimental studies (4 papers), Computational Physics and Python Applications (2 papers) and Stellar, planetary, and galactic studies (1 paper). M. Pettee is often cited by papers focused on Particle physics theoretical and experimental studies (4 papers), Computational Physics and Python Applications (2 papers) and Stellar, planetary, and galactic studies (1 paper). M. Pettee collaborates with scholars based in United States, Canada and Germany. M. Pettee's co-authors include Benjamin Nachman, V. M. Mikuni, David Shih, Gregor Kasieczka, Shirley Ho, François Lanusse, Siavash Golkar, Géraud Krawezik, Michael Eickenberg and Liam Parker and has published in prestigious journals such as Monthly Notices of the Royal Astronomical Society, Journal of High Energy Physics and Physical review. D.

In The Last Decade

M. Pettee

6 papers receiving 95 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
M. Pettee United States	5	58	33	9	8	8	6	101
G. Quétant Switzerland	4	46 0.8×	17 0.5×	11 1.2×	6 0.8×	4 0.5×	7	71
J. A. Raine Switzerland	10	142 2.4×	59 1.8×	15 1.7×	8 1.0×	6 0.8×	19	179
K. Zoch Switzerland	4	65 1.1×	24 0.7×	6 0.7×	4 0.5×	3 0.4×	5	78
L. Rustige Germany	6	67 1.2×	26 0.8×	19 2.1×	14 1.8×	12 1.5×	7	99
N. Chernyavskaya Switzerland	6	87 1.5×	53 1.6×	14 1.6×	5 0.6×	7 0.9×	13	112
W. Korcari Germany	5	91 1.6×	33 1.0×	19 2.1×	4 0.5×	10 1.3×	7	119
R. Kansal United States	4	54 0.9×	44 1.3×	16 1.8×	4 0.5×	5 0.6×	9	78
S. Giagu Italy	5	27 0.5×	17 0.5×	8 0.9×	11 1.4×	3 0.4×	24	67
C. Li China	5	89 1.5×	35 1.1×	7 0.8×	3 0.4×	9 1.1×	10	115
Sergei Gleyzer United States	6	62 1.1×	29 0.9×	3 0.3×	12 1.5×	5 0.6×	26	95

Countries citing papers authored by M. Pettee

Since Specialization

Citations

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

Fields of papers citing papers by M. Pettee

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. Pettee

This figure shows the co-authorship network connecting the top 25 collaborators of M. Pettee. A scholar is included among the top collaborators of M. Pettee 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 M. Pettee. M. Pettee 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.

Parker, Liam, François Lanusse, Siavash Golkar, et al.. (2024). AstroCLIP: a cross-modal foundation model for galaxies. Monthly Notices of the Royal Astronomical Society. 531(4). 4990–5011. 19 indexed citations

2.

Pettee, M., et al.. (2024). Learning likelihood ratios with neural network classifiers. Journal of High Energy Physics. 2024(2). 10 indexed citations

3.

Mikuni, V. M., Benjamin Nachman, & M. Pettee. (2023). Fast point cloud generation with diffusion models in high energy physics. Physical review. D. 108(3). 46 indexed citations

4.

Ju, X., et al.. (2023). Heterogeneous Graph Neural Network for identifying hadronically decayed tau leptons at the High Luminosity LHC. Journal of Instrumentation. 18(7). P07001–P07001. 6 indexed citations

5.

Kasieczka, Gregor, et al.. (2023). Anomaly detection under coordinate transformations. Physical review. D. 107(1). 16 indexed citations

6.

Pettee, M., et al.. (2023). Weakly supervised anomaly detection in the Milky Way. Monthly Notices of the Royal Astronomical Society. 527(3). 8459–8474. 4 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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