M. Pettee
Impact in
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- Particle physics theoretical and experimental studies
- High-Energy Particle Collisions Research
- Particle Detector Development and Performance
- Quantum Chromodynamics and Particle Interactions
- Astrophysics and Cosmic Phenomena
- Neutrino Physics Research
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- Computational Physics and Python Applications
- Gaussian Processes and Bayesian Inference
Papers in
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- Particle physics theoretical and experimental studies 4
- Quantum Chromodynamics and Particle Interactions 1
- Neutrino Physics Research 1
- Particle Detector Development and Performance 1
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- Video Surveillance and Tracking Methods 1
- Advanced Vision and Imaging 1
- Co-authors
- Benjamin Nachman (4 shared papers)V. M. Mikuni (2 shared papers)David Shih (2 shared papers)Gregor Kasieczka (1 shared paper)Michael Eickenberg (1 shared paper)Shirley Ho (1 shared paper)Géraud Krawezik (1 shared paper)Siavash Golkar (1 shared paper)
- Journals
- Physical review. D (2 papers)Monthly Notices of the Royal Astronomical Society (2 papers)Journal of Instrumentation (1 paper)Journal of High Energy Physics (1 paper)
- Partner nations
- United StatesCanadaGermany
In The Last Decade
M. Pettee
6 papers receiving 95 citations
Peers
Comparison fields: 5 of 42
- Nuclear and High Energy Physics 58
- Artificial Intelligence 33
- Instrumentation 3
- Health Informatics 1
- Statistical and Nonlinear Physics 8
Countries citing papers authored by M. Pettee
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
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-authors
The 17 scholars most cited alongside M. Pettee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 46 | |
| 2 | 2024 | 19 | |
| 3 | 2023 | 16 | |
| 4 | 2024 | 10 | |
| 5 | 2023 | 6 | |
| 6 | 2023 | 4 |
About M. Pettee
M. Pettee is a scholar working on Nuclear and High Energy Physics, Computer Vision and Pattern Recognition, Artificial Intelligence, Molecular Biology and Astronomy and Astrophysics, having authored 6 papers that have together received 101 indexed citations. Recurring topics across this work include Particle physics theoretical and experimental studies (4 papers), Computational Physics and Python Applications (2 papers), Quantum Chromodynamics and Particle Interactions (1 paper), Neutrino Physics Research (1 paper), Video Surveillance and Tracking Methods (1 paper), Particle Detector Development and Performance (1 paper), CCD and CMOS Imaging Sensors (1 paper) and Advanced Vision and Imaging (1 paper). The work is most often cited by research in Nuclear and High Energy Physics (58 citations), Artificial Intelligence (33 citations), Instrumentation (3 citations), Health Informatics (1 citation) and Statistical and Nonlinear Physics (8 citations). M. Pettee has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include Benjamin Nachman, V. M. Mikuni, David Shih, Gregor Kasieczka, Michael Eickenberg, Shirley Ho, Géraud Krawezik, Siavash Golkar, Michael T. McCabe and Matthew R. Buckley. Their work appears in journals such as Physical review. D, Monthly Notices of the Royal Astronomical Society, Journal of Instrumentation and Journal of High Energy Physics.
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.