Oliver Eberle
Impact in
- Artificial Intelligence top 10%
- Explainable Artificial Intelligence (XAI)
- Advanced Graph Neural Networks
- Topic Modeling
- Adversarial Robustness in Machine Learning
- Anomaly Detection Techniques and Applications
- Machine Learning in Healthcare
Papers in
-
- Explainable Artificial Intelligence (XAI) 4
- Topic Modeling 4
- Advanced Graph Neural Networks 2
- Natural Language Processing Techniques 2
-
- Time Series Analysis and Forecasting 3
- Co-authors
- Grégoire Montavon (7 shared papers)Kristof T. Schütt (2 shared papers)Shinichi Nakajima (2 shared papers)Jonas Lederer (2 shared papers)Klaus-Robert Müller (2 shared papers)Klaus‐Robert Müller (6 shared papers)Matteo Valleriani (4 shared papers)Anders Søgaard (1 shared paper)
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (2 papers)Science Advances (1 paper)Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (1 paper)arXiv (Cornell University) (1 paper)Datenbank-Spektrum (1 paper)
- Partner nations
- GermanySouth KoreaIsrael
In The Last Decade
Oliver Eberle
9 papers receiving 239 citations
Peers
Comparison fields: 5 of 57
- Artificial Intelligence 174
- Health Informatics 6
- Information Systems and Management 11
- Signal Processing 17
- Computer Vision and Pattern Recognition 31
Countries citing papers authored by Oliver Eberle
This map shows the geographic impact of Oliver Eberle'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 Oliver Eberle with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Oliver Eberle more than expected).
Fields of papers citing papers by Oliver Eberle
This network shows the impact of papers produced by Oliver Eberle. 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 Oliver Eberle. The network helps show where Oliver Eberle may publish in the future.
Co-authors
The 13 scholars most cited alongside Oliver Eberle, 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 | 155 | |
| 2 | 2020 | 43 | |
| 3 | XAI for Graphs: Explaining Graph Neural Network Predictions by Identifying Relevant Walks | 2020 | 15 |
| 4 | 2022 | 11 | |
| 5 | 2023 | 5 | |
| 6 | 2022 | 4 | |
| 7 | 2024 | 3 | |
| 8 | 2024 | 3 | |
| 9 | 2023 | 2 | |
| 10 | 2024 | 0 | |
| 11 | 2024 | 0 |
About Oliver Eberle
Oliver Eberle is a scholar working on Artificial Intelligence, Signal Processing, Molecular Biology, Computer Vision and Pattern Recognition and Materials Chemistry, having authored 11 papers that have together received 241 indexed citations. Recurring topics across this work include Explainable Artificial Intelligence (XAI) (4 papers), Topic Modeling (4 papers), Time Series Analysis and Forecasting (3 papers), Advanced Graph Neural Networks (2 papers), Natural Language Processing Techniques (2 papers), Biomedical Text Mining and Ontologies (2 papers), Machine Learning in Materials Science (2 papers) and Multimodal Machine Learning Applications (1 paper). The work is most often cited by research in Artificial Intelligence (174 citations), Health Informatics (6 citations), Information Systems and Management (11 citations), Signal Processing (17 citations) and Computer Vision and Pattern Recognition (31 citations). Oliver Eberle has collaborated with scholars based in Germany, South Korea and Israel. Frequent co-authors include Grégoire Montavon, Kristof T. Schütt, Shinichi Nakajima, Jonas Lederer, Klaus-Robert Müller, Klaus‐Robert Müller, Matteo Valleriani, Anders Søgaard, Stephanie Brandl and Ilias Chalkidis. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Science Advances, Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), arXiv (Cornell University) and Datenbank-Spektrum.
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.