Daniel Zügner

41 total papers · 2.7k total citations
9 papers, 129 citations indexed

Daniel Zügner is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Molecular Biology. According to data from OpenAlex, Daniel Zügner has authored 9 papers receiving a total of 129 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 2 papers in Statistical and Nonlinear Physics and 1 paper in Molecular Biology. Recurrent topics in Daniel Zügner’s work include Adversarial Robustness in Machine Learning (5 papers), Advanced Graph Neural Networks (3 papers) and Anomaly Detection Techniques and Applications (2 papers). Daniel Zügner is often cited by papers focused on Adversarial Robustness in Machine Learning (5 papers), Advanced Graph Neural Networks (3 papers) and Anomaly Detection Techniques and Applications (2 papers). Daniel Zügner collaborates with scholars based in Germany, Netherlands and United States. Daniel Zügner's co-authors include Stephan Günnemann, Amir Akbarnejad, Oliver Borchert, Marco Orsini Federici, Victor García Satorras, Cecilia Clementi, Robert Pinsler, Chin‐Wei Huang, Rianne van den Berg and Frank Noé and has published in prestigious journals such as Journal of Chemical Theory and Computation, ACM Transactions on Knowledge Discovery from Data and arXiv (Cornell University).