Mathias Lechner
Impact in
- Artificial Intelligence top 5%
- Neural Networks and Applications
- Reinforcement Learning in Robotics
- Adversarial Robustness in Machine Learning
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- Model Reduction and Neural Networks
Papers in
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- Adversarial Robustness in Machine Learning 8
- Neural Networks and Applications 7
- Reinforcement Learning in Robotics 5
- Domain Adaptation and Few-Shot Learning 2
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- Model Reduction and Neural Networks 8
- Co-authors
- Ramin Hasani (15 shared papers)Daniela Rus (13 shared papers)Alexander Amini (7 shared papers)Radu Grosu (9 shared papers)Thomas A. Henzinger (9 shared papers)Aaron Ray (3 shared papers)Max Tschaikowski (2 shared papers)Gerald Teschl (2 shared papers)
- Journals
- Nature Machine Intelligence (3 papers)IEEE Robotics and Automation Letters (1 paper)Science Robotics (1 paper)arXiv (Cornell University) (2 papers)Proceedings of the AAAI Conference on Artificial Intelligence (7 papers)
- Partner nations
- AustriaUnited StatesPoland
In The Last Decade
Mathias Lechner
22 papers receiving 446 citations
Peers
Comparison fields: 5 of 88
- Artificial Intelligence 202
- Statistical and Nonlinear Physics 55
- Health Informatics 6
- Automotive Engineering 50
- Control and Systems Engineering 87
Countries citing papers authored by Mathias Lechner
This map shows the geographic impact of Mathias Lechner'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 Mathias Lechner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mathias Lechner more than expected).
Fields of papers citing papers by Mathias Lechner
This network shows the impact of papers produced by Mathias Lechner. 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 Mathias Lechner. The network helps show where Mathias Lechner may publish in the future.
Co-authors
The 17 scholars most cited alongside Mathias Lechner, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 130 | |
| 2 | 2021 | 119 | |
| 3 | 2022 | 69 | |
| 4 | 2023 | 33 | |
| 5 | 2022 | 21 | |
| 6 | 2019 | 18 | |
| 7 | 2021 | 12 | |
| 8 | 2022 | 10 | |
| 9 | 2023 | 8 | |
| 10 | 2020 | 8 | |
| 11 | 2020 | 6 | |
| 12 | 2021 | 5 | |
| 13 | Learning Long-Term Dependencies in Irregularly-Sampled Time Series | 2020 | 4 |
| 14 | 2023 | 4 | |
| 15 | 2012 | 3 | |
| 16 | 2023 | 2 | |
| 17 | 2023 | 1 | |
| 18 | 2023 | 1 | |
| 19 | 2021 | 1 | |
| 20 | 2020 | 1 |
About Mathias Lechner
Mathias Lechner is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Control and Systems Engineering, Cognitive Neuroscience and Electrical and Electronic Engineering, having authored 22 papers that have together received 458 indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (8 papers), Adversarial Robustness in Machine Learning (8 papers), Neural Networks and Applications (7 papers), Reinforcement Learning in Robotics (5 papers), Fault Detection and Control Systems (4 papers), Robot Manipulation and Learning (3 papers), Neural dynamics and brain function (3 papers) and Domain Adaptation and Few-Shot Learning (2 papers). The work is most often cited by research in Artificial Intelligence (202 citations), Statistical and Nonlinear Physics (55 citations), Health Informatics (6 citations), Automotive Engineering (50 citations) and Control and Systems Engineering (87 citations). Mathias Lechner has collaborated with scholars based in Austria, United States and Poland. Frequent co-authors include Ramin Hasani, Daniela Rus, Alexander Amini, Radu Grosu, Thomas A. Henzinger, Aaron Ray, Max Tschaikowski, Gerald Teschl, Krishnendu Chatterjee and Manuel Zimmer. Their work appears in journals such as Nature Machine Intelligence, IEEE Robotics and Automation Letters, Science Robotics, arXiv (Cornell University) and Proceedings of the AAAI Conference on Artificial Intelligence.
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.