Andreas Gerhardus
Impact in
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- Black Holes and Theoretical Physics
- Dark Matter and Cosmic Phenomena
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- Climate variability and models
Papers in
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- Bayesian Modeling and Causal Inference 4
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- Algebraic Geometry and Number Theory 2
- Algebraic structures and combinatorial models 1
- Co-authors
- Jakob Runge (8 shared papers)Gherardo Varando (3 shared papers)Gustau Camps‐Valls (3 shared papers)Veronika Eyring (4 shared papers)Hans Jockers (3 shared papers)Dmitry Budker (1 shared paper)Laure Zanna (1 shared paper)Emili Balaguer‐Ballester (1 shared paper)
- Journals
- Nature Reviews Earth & Environment (2 papers)Nuclear Physics B (2 papers)Physics Reports (1 paper)Journal of Geometry and Physics (1 paper)The Annals of Statistics (1 paper)
- Partner nations
- GermanySpainUnited States
In The Last Decade
Andreas Gerhardus
12 papers receiving 278 citations
Andreas Gerhardus's Hit Papers
Peers
Comparison fields: 5 of 82
- Nuclear and High Energy Physics 41
- Global and Planetary Change 63
- Geometry and Topology 21
- Statistical and Nonlinear Physics 29
- Atmospheric Science 36
Countries citing papers authored by Andreas Gerhardus
This map shows the geographic impact of Andreas Gerhardus'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 Andreas Gerhardus with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andreas Gerhardus more than expected).
Fields of papers citing papers by Andreas Gerhardus
This network shows the impact of papers produced by Andreas Gerhardus. 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 Andreas Gerhardus. The network helps show where Andreas Gerhardus may publish in the future.
Co-authors
The 19 scholars most cited alongside Andreas Gerhardus, 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 | Causal inference for time series Hit paper breakdown → | 2023 | 134 |
| 2 | 2023 | 57 | |
| 3 | 2016 | 30 | |
| 4 | 2016 | 18 | |
| 5 | 2021 | 12 | |
| 6 | 2022 | 9 | |
| 7 | 2016 | 7 | |
| 8 | 2023 | 6 | |
| 9 | 2024 | 3 | |
| 10 | 2018 | 3 | |
| 11 | 2023 | 1 | |
| 12 | 2024 | 1 | |
| 13 | 2021 | 0 |
About Andreas Gerhardus
Andreas Gerhardus is a scholar working on Artificial Intelligence, Geometry and Topology, Statistical and Nonlinear Physics, Global and Planetary Change and Signal Processing, having authored 13 papers that have together received 281 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (4 papers), Black Holes and Theoretical Physics (2 papers), Nonlinear Waves and Solitons (2 papers), Algebraic Geometry and Number Theory (2 papers), Time Series Analysis and Forecasting (2 papers), Atmospheric and Environmental Gas Dynamics (2 papers), Algebraic structures and combinatorial models (1 paper) and Tropical and Extratropical Cyclones Research (1 paper). The work is most often cited by research in Nuclear and High Energy Physics (41 citations), Global and Planetary Change (63 citations), Geometry and Topology (21 citations), Statistical and Nonlinear Physics (29 citations) and Atmospheric Science (36 citations). Andreas Gerhardus has collaborated with scholars based in Germany, Spain and United States. Frequent co-authors include Jakob Runge, Gherardo Varando, Gustau Camps‐Valls, Veronika Eyring, Hans Jockers, Dmitry Budker, Laure Zanna, Emili Balaguer‐Ballester, Y. V. Stadnik and N. Leefer. Their work appears in journals such as Nature Reviews Earth & Environment, Nuclear Physics B, Physics Reports, Journal of Geometry and Physics and The Annals of Statistics.
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.