Florian Mai
Impact in
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- Topic Modeling
- Natural Language Processing Techniques
- Speech Recognition and Synthesis
- Advanced Text Analysis Techniques
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- Multimodal Machine Learning Applications
Papers in
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- Topic Modeling 5
- Advanced Text Analysis Techniques 2
- Speech Recognition and Synthesis 2
- Natural Language Processing Techniques 2
- Artificial Intelligence in Games 1
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- Multimodal Machine Learning Applications 1
- Co-authors
- James Henderson (2 shared papers)François Fleuret (3 shared papers)Nikolaos Pappas (1 shared paper)Noah A. Smith (1 shared paper)Ansgar Scherp (3 shared papers)Petr Motlíček (1 shared paper)Titouan Parcollet (1 shared paper)Martin Jaggi (2 shared papers)
- Journals
- ChemCatChem (1 paper)Journal of Inorganic Biochemistry (1 paper)Chemical Engineering & Technology (1 paper)ZBW Publication Archive (ZBW – Leibniz Information Centre for Economics) (3 papers)Infoscience (Ecole Polytechnique Fédérale de Lausanne) (3 papers)
- Partner nations
- GermanySwitzerlandUnited States
In The Last Decade
Florian Mai
9 papers receiving 57 citations
Peers
Comparison fields: 5 of 29
- Artificial Intelligence 46
- Computer Vision and Pattern Recognition 16
- Catalysis 5
- Signal Processing 7
- Information Systems 9
Countries citing papers authored by Florian Mai
This map shows the geographic impact of Florian Mai'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 Florian Mai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Florian Mai more than expected).
Fields of papers citing papers by Florian Mai
This network shows the impact of papers produced by Florian Mai. 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 Florian Mai. The network helps show where Florian Mai may publish in the future.
Co-authors
The 17 scholars most cited alongside Florian Mai, 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 | 2020 | 15 | |
| 2 | 2023 | 8 | |
| 3 | 2023 | 7 | |
| 4 | Optimizer Benchmarking Needs to Account for Hyperparameter Tuning | 2020 | 7 |
| 5 | 2017 | 7 | |
| 6 | 2022 | 6 | |
| 7 | On the Tunability of Optimizers in Deep Learning | 2019 | 4 |
| 8 | 2018 | 4 | |
| 9 | 2017 | 2 | |
| 10 | 2025 | 0 | |
| 11 | 2025 | 0 | |
| 12 | 2023 | 0 |
About Florian Mai
Florian Mai is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Materials Chemistry, Molecular Biology and Information Systems, having authored 12 papers that have together received 60 indexed citations. Recurring topics across this work include Topic Modeling (5 papers), Catalytic Processes in Materials Science (2 papers), Advanced Text Analysis Techniques (2 papers), Speech Recognition and Synthesis (2 papers), Natural Language Processing Techniques (2 papers), Pneumocystis jirovecii pneumonia detection and treatment (1 paper), Multimodal Machine Learning Applications (1 paper) and Artificial Intelligence in Games (1 paper). The work is most often cited by research in Artificial Intelligence (46 citations), Computer Vision and Pattern Recognition (16 citations), Catalysis (5 citations), Signal Processing (7 citations) and Information Systems (9 citations). Florian Mai has collaborated with scholars based in Germany, Switzerland and United States. Frequent co-authors include James Henderson, François Fleuret, Nikolaos Pappas, Noah A. Smith, Ansgar Scherp, Petr Motlíček, Titouan Parcollet, Martin Jaggi, Juan Zuluaga-Gómez and Thijs Vogels. Their work appears in journals such as ChemCatChem, Journal of Inorganic Biochemistry, Chemical Engineering & Technology, ZBW Publication Archive (ZBW – Leibniz Information Centre for Economics) and Infoscience (Ecole Polytechnique Fédérale de Lausanne).
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.