Mathias Lechner
Impact in
- Artificial Intelligence top 5%
- Adversarial Robustness in Machine Learning
- Neural Networks and Applications
- Reinforcement Learning in Robotics
Papers in
-
- Adversarial Robustness in Machine Learning 11
- Neural Networks and Applications 8
- Reinforcement Learning in Robotics 6
-
- Model Reduction and Neural Networks 10
- Co-authors
- Ramin Hasani (16 shared papers)Daniela Rus (14 shared papers)Alexander Amini (7 shared papers)Radu Grosu (10 shared papers)Thomas A. Henzinger (12 shared papers)Aaron Ray (3 shared papers)Krishnendu Chatterjee (6 shared papers)Max Tschaikowski (2 shared papers)
- Journals
- Nature Machine Intelligence (3 papers)IEEE Robotics and Automation Letters (1 paper)Science Robotics (1 paper)Lecture notes in physics (1 paper)Lecture notes in computer science (4 papers)
- Partner nations
- AustriaUnited StatesDenmark
In The Last Decade
Mathias Lechner
28 papers receiving 638 citations
Peers
Comparison fields: 5 of 91
- Artificial Intelligence 284
- Health Informatics 8
- Statistical and Nonlinear Physics 65
- Software 22
- Automotive Engineering 59
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 24 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 29 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 150 | |
| 2 | 2021 | 149 | |
| 3 | 2022 | 85 | |
| 4 | 2023 | 47 | |
| 5 | 2022 | 24 | |
| 6 | 2019 | 24 | |
| 7 | 2021 | 20 | |
| 8 | 2022 | 19 | |
| 9 | 2020 | 18 | |
| 10 | 2023 | 16 | |
| 11 | 2001 | 13 | |
| 12 | 2021 | 11 | |
| 13 | 2001 | 11 | |
| 14 | 2020 | 11 | |
| 15 | 2020 | 8 | |
| 16 | 2023 | 7 | |
| 17 | 2023 | 6 | |
| 18 | 2020 | 6 | |
| 19 | 2022 | 5 | |
| 20 | Learning Long-Term Dependencies in Irregularly-Sampled Time Series | 2020 | 4 |
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 29 papers that have together received 652 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (11 papers), Model Reduction and Neural Networks (10 papers), Neural Networks and Applications (8 papers), Reinforcement Learning in Robotics (6 papers), Fault Detection and Control Systems (5 papers), Neural dynamics and brain function (3 papers), Robot Manipulation and Learning (3 papers) and Formal Methods in Verification (3 papers). The work is most often cited by research in Artificial Intelligence (284 citations), Health Informatics (8 citations), Statistical and Nonlinear Physics (65 citations), Software (22 citations) and Automotive Engineering (59 citations). Mathias Lechner has collaborated with scholars based in Austria, United States and Denmark. Frequent co-authors include Ramin Hasani, Daniela Rus, Alexander Amini, Radu Grosu, Thomas A. Henzinger, Aaron Ray, Krishnendu Chatterjee, Max Tschaikowski, Gerald Teschl and Lucas Liebenwein. Their work appears in journals such as Nature Machine Intelligence, IEEE Robotics and Automation Letters, Science Robotics, Lecture notes in physics and Lecture notes in computer science.
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.