Matthias Bauer
- Computer Science Applications top 10%
- Artificial Intelligence
- Education
- Molecular Biology
- Computer Vision and Pattern Recognition
- Co-authors
- Christoph MeinelThomas StaubitzJan RenzErwin FreyMatthias LechnerPeter PicklRichard E. TurnerSebastian Nowozin
- Topics
- Online Learning and Analytics (4 papers)Online and Blended Learning (4 papers)Multimedia Communication and Technology (4 papers)
- Cited by
- Computer Science ApplicationsArtificial IntelligenceDevelopmental and Educational Psychology
- Journals
- eLifearXiv (Cornell University)publish.UP (University of Potsdam)
- Partner nations
- GermanyUnited Kingdom
In The Last Decade
Matthias Bauer
14 papers receiving 111 citations
Peers
Comparison fields: 5 of 48
- Computer Science Applications 40
- Artificial Intelligence 36
- Education 30
- Molecular Biology 23
- Computer Vision and Pattern Recognition 17
Countries citing papers authored by Matthias Bauer
This map shows the geographic impact of Matthias Bauer'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 Bauer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthias Bauer more than expected).
Fields of papers citing papers by Matthias Bauer
This network shows the impact of papers produced by Matthias Bauer. 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 Bauer. The network helps show where Matthias Bauer may publish in the future.
Co-authorship network of co-authors of Matthias Bauer
This figure shows the co-authorship network connecting the top 25 collaborators of Matthias Bauer. A scholar is included among the top collaborators of Matthias Bauer 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 Matthias Bauer. Matthias Bauer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Learning Invariances using the Marginal Likelihood | 6 |
| 2 | 22 | |
| 3 | Decision-Theoretic Meta-Learning: Versatile and Efficient Amortization of Few-Shot Learning. | 1 |
| 4 | Versa: Versatile and Efficient Few-shot Learning | 3 |
| 5 | 3 | |
| 6 | 31 | |
| 7 | 38 | |
| 8 | 3 | |
| 9 | OPTIMIZING THE VIDEO EXPERIENCE IN MOOCS | 3 |
| 10 | 2 | |
| 11 | 2 | |
| 12 | 1 | |
| 13 | 1 | |
| 14 | Connected Media Experiences: interactive video using Linked Data on the Web | 1 |
About Matthias Bauer
Matthias Bauer is a scholar working on Computer Science Applications, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 14 papers that have together received 117 indexed citations. Recurring topics across this work include Online Learning and Analytics (4 papers), Online and Blended Learning (4 papers) and Multimedia Communication and Technology (4 papers). The work is most often cited by research in Computer Science Applications (40 citations), Artificial Intelligence (36 citations) and Developmental and Educational Psychology (14 citations). Matthias Bauer has collaborated with scholars based in Germany and United Kingdom. Frequent co-authors include Christoph Meinel, Thomas Staubitz, Jan Renz, Erwin Frey, Matthias Lechner, Peter Pickl, Richard E. Turner, Sebastian Nowozin, Jonathan Gordon and Mark van der Wilk. Their work appears in journals such as eLife, arXiv (Cornell University) and publish.UP (University of Potsdam).
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.