Maxime Rischard
Impact in
- Instrumentation top 10%
- Astronomy and Astrophysical Research
- Astronomy and Astrophysics top 10%
- Stellar, planetary, and galactic studies
- Gamma-ray bursts and supernovae
- Galaxies: Formation, Evolution, Phenomena
Papers in
-
- Anomaly Detection Techniques and Applications 1
- Gaussian Processes and Bayesian Inference 1
-
- Advanced Multi-Objective Optimization Algorithms 2
- Co-authors
- D. Starr (2 shared papers)N. Butler (2 shared papers)J. S. Bloom (2 shared papers)John M. Brewer (1 shared paper)Arien Crellin-Quick (1 shared paper)Joseph W. Richards (1 shared paper)Rachel Kennedy (1 shared paper)Luke Miratrix (2 shared papers)
- Journals
- Journal of Statistical Software (1 paper)The Astrophysical Journal (1 paper)Journal of Statistical Planning and Inference (1 paper)Journal of the American Statistical Association (1 paper)Astronomische Nachrichten (1 paper)
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Maxime Rischard
5 papers receiving 222 citations
Peers
Comparison fields: 5 of 58
- Instrumentation 60
- Astronomy and Astrophysics 132
- Signal Processing 37
- Statistics and Probability 24
- Computational Mechanics 50
Countries citing papers authored by Maxime Rischard
This map shows the geographic impact of Maxime Rischard'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 Maxime Rischard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maxime Rischard more than expected).
Fields of papers citing papers by Maxime Rischard
This network shows the impact of papers produced by Maxime Rischard. 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 Maxime Rischard. The network helps show where Maxime Rischard may publish in the future.
Co-authors
The 13 scholars most cited alongside Maxime Rischard, 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 | 2011 | 184 | |
| 2 | 2019 | 15 | |
| 3 | 2022 | 12 | |
| 4 | 2008 | 11 | |
| 5 | 2020 | 7 |
About Maxime Rischard
Maxime Rischard is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Economics and Econometrics, Astronomy and Astrophysics and Statistical and Nonlinear Physics, having authored 5 papers that have together received 229 indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (2 papers), Stellar, planetary, and galactic studies (1 paper), Plant Water Relations and Carbon Dynamics (1 paper), Housing Market and Economics (1 paper), Astronomical Observations and Instrumentation (1 paper), Anomaly Detection Techniques and Applications (1 paper), Gaussian Processes and Bayesian Inference (1 paper) and Economic and Environmental Valuation (1 paper). The work is most often cited by research in Instrumentation (60 citations), Astronomy and Astrophysics (132 citations), Signal Processing (37 citations), Statistics and Probability (24 citations) and Computational Mechanics (50 citations). Maxime Rischard has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include D. Starr, N. Butler, J. S. Bloom, John M. Brewer, Arien Crellin-Quick, Joseph W. Richards, Rachel Kennedy, Luke Miratrix, Luke Bornn and Johanni Brea. Their work appears in journals such as Journal of Statistical Software, The Astrophysical Journal, Journal of Statistical Planning and Inference, Journal of the American Statistical Association and Astronomische Nachrichten.
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.