Daniel Zügner
Impact in
- Artificial Intelligence top 5%
- Advanced Graph Neural Networks
- Adversarial Robustness in Machine Learning
- Topic Modeling
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- Complex Network Analysis Techniques
Papers in
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- Adversarial Robustness in Machine Learning 7
- Advanced Graph Neural Networks 4
- Anomaly Detection Techniques and Applications 2
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- Complex Network Analysis Techniques 2
- Co-authors
- Stephan Günnemann (9 shared papers)Amir Akbarnejad (4 shared papers)Oliver Borchert (1 shared paper)Michele Catasta (1 shared paper)Jure Leskovec (1 shared paper)Tobias Kirschstein (1 shared paper)Marco Orsini Federici (1 shared paper)Victor García Satorras (1 shared paper)
- Journals
- ACM Transactions on Knowledge Discovery from Data (1 paper)Journal of Chemical Theory and Computation (1 paper)Gesellschaft für Informatik (GI) (1 paper)arXiv (Cornell University) (2 papers)Neural Information Processing Systems (2 papers)
- Partner nations
- GermanyNetherlandsUnited Kingdom
In The Last Decade
Daniel Zügner
11 papers receiving 363 citations
Peers
Comparison fields: 5 of 59
- Artificial Intelligence 278
- Statistical and Nonlinear Physics 68
- Computational Mathematics 2
- Signal Processing 32
- Software 11
Countries citing papers authored by Daniel Zügner
This map shows the geographic impact of Daniel Zügner'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 Daniel Zügner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Zügner more than expected).
Fields of papers citing papers by Daniel Zügner
This network shows the impact of papers produced by Daniel Zügner. 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 Daniel Zügner. The network helps show where Daniel Zügner may publish in the future.
Co-authors
The 18 scholars most cited alongside Daniel Zügner, 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 | 2019 | 165 | |
| 2 | 2020 | 59 | |
| 3 | 2023 | 48 | |
| 4 | 2021 | 41 | |
| 5 | 2020 | 24 | |
| 6 | NetGAN: Generating Graphs via Random Walks | 2018 | 13 |
| 7 | Pushing the limits of RFID: Empowering RFID-based Electronic Article Surveillance with Data Analytics Techniques | 2015 | 11 |
| 8 | Adversarial Attacks on Classification Models for Graphs | 2018 | 5 |
| 9 | Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts | 2020 | 3 |
| 10 | Reliable Graph Neural Networks via Robust Aggregation | 2020 | 2 |
| 11 | 2019 | 2 |
About Daniel Zügner
Daniel Zügner is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Electrical and Electronic Engineering, Molecular Biology and Social Psychology, having authored 11 papers that have together received 373 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (7 papers), Advanced Graph Neural Networks (4 papers), Complex Network Analysis Techniques (2 papers), Anomaly Detection Techniques and Applications (2 papers), Ferroelectric and Negative Capacitance Devices (1 paper), Indoor and Outdoor Localization Technologies (1 paper), Mental Health via Writing (1 paper) and Advanced Malware Detection Techniques (1 paper). The work is most often cited by research in Artificial Intelligence (278 citations), Statistical and Nonlinear Physics (68 citations), Computational Mathematics (2 citations), Signal Processing (32 citations) and Software (11 citations). Daniel Zügner has collaborated with scholars based in Germany, Netherlands and United Kingdom. Frequent co-authors include Stephan Günnemann, Amir Akbarnejad, Oliver Borchert, Michele Catasta, Jure Leskovec, Tobias Kirschstein, Marco Orsini Federici, Victor García Satorras, Chin‐Wei Huang and Cecilia Clementi. Their work appears in journals such as ACM Transactions on Knowledge Discovery from Data, Journal of Chemical Theory and Computation, Gesellschaft für Informatik (GI), arXiv (Cornell University) and Neural Information Processing Systems.
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.