Stephan Günnemann
- Artificial Intelligence top 0.5%
- Statistical and Nonlinear Physics top 1%
- Information Systems top 1%
- Computer Vision and Pattern Recognition top 2%
- Signal Processing top 2%
- Co-authors
- Thomas SeidlAleksandar BojchevskiEmmanuel MüllerDaniel ZügnerJohannes KlicperaInes FärberIra AssentAmir Akbarnejad
- Topics
- Complex Network Analysis Techniques (32 papers)Advanced Clustering Algorithms Research (30 papers)Data Management and Algorithms (26 papers)
- Partner nations
- GermanyUnited StatesDenmark
In The Last Decade
Stephan Günnemann
122 papers receiving 2.3k citations
Hit Papers
Peers
Comparison fields: 5 of 135
- Artificial Intelligence 1.6k
- Statistical and Nonlinear Physics 579
- Information Systems 489
- Computer Vision and Pattern Recognition 471
- Signal Processing 440
Countries citing papers authored by Stephan Günnemann
This map shows the geographic impact of Stephan Günnemann'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 Stephan Günnemann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephan Günnemann more than expected).
Fields of papers citing papers by Stephan Günnemann
This network shows the impact of papers produced by Stephan Günnemann. 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 Stephan Günnemann. The network helps show where Stephan Günnemann may publish in the future.
Co-authorship network of co-authors of Stephan Günnemann
This figure shows the co-authorship network connecting the top 25 collaborators of Stephan Günnemann. A scholar is included among the top collaborators of Stephan Günnemann based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Stephan Günnemann. Stephan Günnemann is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | Predicting cellular responses to complex perturbations in high‐throughput screensbreakdown → | 97 |
| 3 | 47 | |
| 4 | 1 | |
| 5 | Directional Message Passing on Molecular Graphs via Synthetic Coordinates | 5 |
| 6 | Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and More | 3 |
| 7 | Deep Rao-Blackwellised Particle Filters for Time Series Forecasting | 8 |
| 8 | Fast and Flexible Temporal Point Processes with Triangular Maps | 2 |
| 9 | 15 | |
| 10 | Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift | 22 |
| 11 | Uncertainty on Asynchronous Time Event Prediction | 2 |
| 12 | Combining Neural Networks with Personalized PageRank for Classification on Graphs | 31 |
| 13 | Predict then Propagate: Combining neural networks with personalized pagerank for classification on graphs | 3 |
| 14 | Adversarial Attacks on Classification Models for Graphs | 5 |
| 15 | Predict then Propagate: Graph Neural Networks meet Personalized PageRank | 122 |
| 16 | Personalized Embedding Propagation: Combining Neural Networks on Graphs with Personalized PageRank. | 7 |
| 17 | Deep Gaussian Embedding of Attributed Graphs: Unsupervised Inductive Learning via Ranking | 16 |
| 18 | Efficient Batched Distance and Centrality Computation in Unweighted and Weighted Graphs. | 1 |
| 19 | Preferential Attachment in Graphs with Affinities | 2 |
| 20 | A framework for evaluation and exploration of clustering algorithms in subspaces of high dimensional databases | 5 |
About Stephan Günnemann
Stephan Günnemann is a scholar working on Signal Processing, Statistical and Nonlinear Physics and Artificial Intelligence, having authored 130 papers that have together received 2.4k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (32 papers), Advanced Clustering Algorithms Research (30 papers) and Data Management and Algorithms (26 papers). The work is most often cited by research in Artificial Intelligence (1.6k citations), Statistical and Nonlinear Physics (579 citations) and Signal Processing (440 citations). Stephan Günnemann has collaborated with scholars based in Germany, United States and Denmark. Frequent co-authors include Thomas Seidl, Aleksandar Bojchevski, Emmanuel Müller, Daniel Zügner, Johannes Klicpera, Ines Färber, Ira Assent, Amir Akbarnejad, Brigitte Boden and Christos Faloutsos. Their work appears in journals such as Scientific Reports, Geophysical Research Letters and Journal of Hydrology.
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.