Marc Fischer
- Radiology, Nuclear Medicine and Imaging
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Cardiology and Cardiovascular Medicine
- Physiology
- Co-authors
- Sergios GatidisTobias HeppBin YangFabian BambergMartin VechevThomas KüstnerKonstantin NikolaouPhilipp Sommer
- Topics
- Radiomics and Machine Learning in Medical Imaging (6 papers)Adversarial Robustness in Machine Learning (3 papers)Advanced Neural Network Applications (3 papers)
- Partner nations
- GermanySwitzerlandUnited Kingdom
In The Last Decade
Marc Fischer
21 papers receiving 229 citations
Peers
Comparison fields: 5 of 77
- Radiology, Nuclear Medicine and Imaging 67
- Artificial Intelligence 66
- Computer Vision and Pattern Recognition 35
- Cardiology and Cardiovascular Medicine 26
- Physiology 25
Countries citing papers authored by Marc Fischer
This map shows the geographic impact of Marc Fischer'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 Marc Fischer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marc Fischer more than expected).
Fields of papers citing papers by Marc Fischer
This network shows the impact of papers produced by Marc Fischer. 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 Marc Fischer. The network helps show where Marc Fischer may publish in the future.
Co-authorship network of co-authors of Marc Fischer
This figure shows the co-authorship network connecting the top 25 collaborators of Marc Fischer. A scholar is included among the top collaborators of Marc Fischer 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 Marc Fischer. Marc Fischer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 15 | |
| 3 | 9 | |
| 4 | 2 | |
| 5 | 13 | |
| 6 | 10 | |
| 7 | 5 | |
| 8 | 4 | |
| 9 | 9 | |
| 10 | 1 | |
| 11 | 32 | |
| 12 | 15 | |
| 13 | 30 | |
| 14 | DL2: Training and Querying Neural Networks with Logic. | 26 |
| 15 | Distilled Agent DQN for Provable Adversarial Robustness | 3 |
| 16 | 10 | |
| 17 | 2 | |
| 18 | 13 | |
| 19 | 6 | |
| 20 | 2 |
About Marc Fischer
Marc Fischer is a scholar working on Hardware and Architecture, Radiology, Nuclear Medicine and Imaging and Industrial and Manufacturing Engineering, having authored 23 papers that have together received 233 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (6 papers), Adversarial Robustness in Machine Learning (3 papers) and Advanced Neural Network Applications (3 papers). The work is most often cited by research in Health Informatics (5 citations), Metals and Alloys (8 citations) and Radiology, Nuclear Medicine and Imaging (67 citations). Marc Fischer has collaborated with scholars based in Germany, Switzerland and United Kingdom. Frequent co-authors include Sergios Gatidis, Tobias Hepp, Bin Yang, Fabian Bamberg, Martin Vechev, Thomas Küstner, Konstantin Nikolaou, Philipp Sommer, Jan Schlechtendahl and Mislav Balunović. Their work appears in journals such as Corrosion Science, Medical Image Analysis and Neural Computing and Applications.
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.