Matthias Plappert
Impact in
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- Robot Manipulation and Learning
- Artificial Intelligence top 5%
- Reinforcement Learning in Robotics
Papers in
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- Robot Manipulation and Learning 2
- Human Motion and Animation 1
- Co-authors
- Szymon SidorBowen BakerArthur J PetronJonas SchneiderWojciech ZarembaRafał JózefowiczJakub PachockiLilian Weng
- Journals
- Robotics and Autonomous Systems (1 paper)The International Journal of Robotics Research (1 paper)Frontiers in Robotics and AI (1 paper)International Conference on Information Fusion (1 paper)International Conference on Learning Representations (1 paper)
- Partner nations
- GermanyUnited Kingdom
In The Last Decade
Matthias Plappert
5 papers receiving 983 citations
Hit Papers
Peers
Comparison fields: 5 of 84
- Control and Systems Engineering 582
- Artificial Intelligence 453
- Computer Vision and Pattern Recognition 234
- Human-Computer Interaction 54
- Biomedical Engineering 289
Countries citing papers authored by Matthias Plappert
This map shows the geographic impact of Matthias Plappert'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 Matthias Plappert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthias Plappert more than expected).
Fields of papers citing papers by Matthias Plappert
This network shows the impact of papers produced by Matthias Plappert. 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 Matthias Plappert. The network helps show where Matthias Plappert may publish in the future.
Co-authors
The 23 scholars most cited alongside Matthias Plappert, 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 | 2021 | 19 | |
| 2 | Learning dexterous in-hand manipulation Hit paper breakdown → | 2019 | 896 |
| 3 | Parameter Space Noise for Exploration | 2018 | 32 |
| 4 | 2018 | 67 | |
| 5 | Dimensionality reduction for whole-body human motion recognition | 2016 | 8 |
About Matthias Plappert
Matthias Plappert is a scholar working on Human-Computer Interaction, Control and Systems Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence and Cognitive Neuroscience, having authored 5 papers that have together received 1.0k indexed citations. Recurring topics across this work include Robot Manipulation and Learning (2 papers), Human Pose and Action Recognition (2 papers), Reinforcement Learning in Robotics (2 papers), Tactile and Sensory Interactions (1 paper), Multimodal Machine Learning Applications (1 paper), Evolutionary Algorithms and Applications (1 paper), Human Motion and Animation (1 paper) and Anomaly Detection Techniques and Applications (1 paper). The work is most often cited by research in Control and Systems Engineering (582 citations), Artificial Intelligence (453 citations), Computer Vision and Pattern Recognition (234 citations), Human-Computer Interaction (54 citations) and Biomedical Engineering (289 citations). Matthias Plappert has collaborated with scholars based in Germany and United Kingdom. Frequent co-authors include Szymon Sidor, Bowen Baker, Arthur J Petron, Jonas Schneider, Wojciech Zaremba, Rafał Józefowicz, Jakub Pachocki, Lilian Weng, Josh Tobin and Peter Welinder. Their work appears in journals such as Robotics and Autonomous Systems, The International Journal of Robotics Research, Frontiers in Robotics and AI, International Conference on Information Fusion and International Conference on Learning Representations.
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.