Patrick Schäfer
Impact in
- Signal Processing top 10%
- Time Series Analysis and Forecasting
- Music and Audio Processing
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- Neurogenesis and neuroplasticity mechanisms
Papers in
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- Time Series Analysis and Forecasting 4
- Music and Audio Processing 2
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- Anomaly Detection Techniques and Applications 2
- Data Stream Mining Techniques 1
- Co-authors
- Matthew Middlehurst (3 shared papers)Anthony Bagnall (3 shared papers)Michael Karl (3 shared papers)Manuela Völkner (1 shared paper)Peter Oertel (1 shared paper)Alex M. Sykes (1 shared paper)Sheik Pran Babu Sardar Pasha (1 shared paper)Yiqing Zhu (1 shared paper)
- Journals
- Glia (2 papers)Data Mining and Knowledge Discovery (2 papers)Scientific Reports (1 paper)Proceedings of the VLDB Endowment (1 paper)WASSERWIRTSCHAFT (1 paper)
- Partner nations
- GermanyUnited KingdomChina
In The Last Decade
Patrick Schäfer
12 papers receiving 176 citations
Patrick Schäfer's Hit Papers
Peers
Comparison fields: 5 of 66
- Signal Processing 53
- Developmental Neuroscience 16
- Ophthalmology 21
- Cellular and Molecular Neuroscience 36
- Artificial Intelligence 49
Countries citing papers authored by Patrick Schäfer
This map shows the geographic impact of Patrick Schäfer'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 Patrick Schäfer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Patrick Schäfer more than expected).
Fields of papers citing papers by Patrick Schäfer
This network shows the impact of papers produced by Patrick Schäfer. 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 Patrick Schäfer. The network helps show where Patrick Schäfer may publish in the future.
Co-authors
The 25 scholars most cited alongside Patrick Schäfer, 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 | 2015 | 60 | |
| 2 | Bake off redux: a review and experimental evaluation of recent time series classification algorithms Hit paper breakdown → | 2024 | 58 |
| 3 | 2017 | 27 | |
| 4 | 2013 | 8 | |
| 5 | 2017 | 7 | |
| 6 | 2024 | 6 | |
| 7 | 2023 | 4 | |
| 8 | 2020 | 4 | |
| 9 | 2024 | 2 | |
| 10 | 2012 | 2 | |
| 11 | 2014 | 1 | |
| 12 | 2025 | 1 |
About Patrick Schäfer
Patrick Schäfer is a scholar working on Signal Processing, Artificial Intelligence, Molecular Biology, Developmental Neuroscience and Cellular and Molecular Neuroscience, having authored 12 papers that have together received 180 indexed citations. Recurring topics across this work include Time Series Analysis and Forecasting (4 papers), Retinal Development and Disorders (3 papers), Neurogenesis and neuroplasticity mechanisms (3 papers), Neuroscience and Neuropharmacology Research (2 papers), Music and Audio Processing (2 papers), Anomaly Detection Techniques and Applications (2 papers), Data Stream Mining Techniques (1 paper) and Advanced Chemical Sensor Technologies (1 paper). The work is most often cited by research in Signal Processing (53 citations), Developmental Neuroscience (16 citations), Ophthalmology (21 citations), Cellular and Molecular Neuroscience (36 citations) and Artificial Intelligence (49 citations). Patrick Schäfer has collaborated with scholars based in Germany, United Kingdom and China. Frequent co-authors include Matthew Middlehurst, Anthony Bagnall, Michael Karl, Manuela Völkner, Peter Oertel, Alex M. Sykes, Sheik Pran Babu Sardar Pasha, Yiqing Zhu, Jörg Seewig and Ulf Leser. Their work appears in journals such as Glia, Data Mining and Knowledge Discovery, Scientific Reports, Proceedings of the VLDB Endowment and WASSERWIRTSCHAFT.
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.