Lars Hertel
Impact in
- Signal Processing top 10%
- Music and Audio Processing
- Speech and Audio Processing
Papers in ⓘ
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- Speech Recognition and Synthesis 5
- Machine Learning and Data Classification 2
- Computational Physics and Python Applications 1
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- Music and Audio Processing 6
- Speech and Audio Processing 6
- Co-authors
- Marco Maaß (6 shared papers)Huy Phan (6 shared papers)Erhardt Barth (1 shared paper)Alfred Mertins (6 shared papers)Thomas Martinetz (2 shared papers)Radoslaw Mazur (6 shared papers)Pierre Baldi (3 shared papers)Peter Reimer (1 shared paper)
- Journals
- IEEE/ACM Transactions on Audio Speech and Language Processing (2 papers)Physical review. D (1 paper)British Journal of Haematology (1 paper)Vision Research (1 paper)The American Journal of Gastroenterology (1 paper)
- Partner nations
- GermanyHungaryUnited States
In The Last Decade
Lars Hertel
17 papers receiving 304 citations
Peers
Comparison fields: 5 of 82
- Signal Processing 94
- Developmental Biology 8
- Computer Vision and Pattern Recognition 69
- Artificial Intelligence 73
- Pulmonary and Respiratory Medicine 75
Countries citing papers authored by Lars Hertel
This map shows the geographic impact of Lars Hertel'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 Lars Hertel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lars Hertel more than expected).
Fields of papers citing papers by Lars Hertel
This network shows the impact of papers produced by Lars Hertel. 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 Lars Hertel. The network helps show where Lars Hertel may publish in the future.
Co-authors
The 25 scholars most cited alongside Lars Hertel, 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 | 2004 | 88 | |
| 2 | 2015 | 72 | |
| 3 | 2017 | 44 | |
| 4 | 2016 | 23 | |
| 5 | 2019 | 17 | |
| 6 | Sherpa: Hyperparameter Optimization for Machine Learning Models | 2018 | 16 |
| 7 | 2015 | 14 | |
| 8 | 2021 | 10 | |
| 9 | 2020 | 7 | |
| 10 | 2017 | 7 | |
| 11 | 2002 | 5 | |
| 12 | 2015 | 4 | |
| 13 | 2015 | 4 | |
| 14 | 2002 | 2 | |
| 15 | On Hyperparameter Optimization for Deep Learning | 2020 | 2 |
| 16 | 2021 | 1 | |
| 17 | 2003 | 1 | |
| 18 | 2025 | 0 |
About Lars Hertel
Lars Hertel is a scholar working on Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Oncology and Computational Theory and Mathematics, having authored 18 papers that have together received 317 indexed citations. Recurring topics across this work include Music and Audio Processing (6 papers), Speech and Audio Processing (6 papers), Speech Recognition and Synthesis (5 papers), Experimental Learning in Engineering (2 papers), Machine Learning and Data Classification (2 papers), Advanced Multi-Objective Optimization Algorithms (2 papers), Particle Detector Development and Performance (1 paper) and Computational Physics and Python Applications (1 paper). The work is most often cited by research in Signal Processing (94 citations), Developmental Biology (8 citations), Computer Vision and Pattern Recognition (69 citations), Artificial Intelligence (73 citations) and Pulmonary and Respiratory Medicine (75 citations). Lars Hertel has collaborated with scholars based in Germany, Hungary and United States. Frequent co-authors include Marco Maaß, Huy Phan, Erhardt Barth, Alfred Mertins, Thomas Martinetz, Radoslaw Mazur, Pierre Baldi, Peter Reimer, Dirk Domagk and Johannes Weßling. Their work appears in journals such as IEEE/ACM Transactions on Audio Speech and Language Processing, Physical review. D, British Journal of Haematology, Vision Research and The American Journal of Gastroenterology.
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.