Hubert Ramsauer
Impact in
-
- Generative Adversarial Networks and Image Synthesis
- Advanced Image Processing Techniques
- Digital Media Forensic Detection
- Advanced Vision and Imaging
- Face recognition and analysis
- Advanced Neural Network Applications
- Image Enhancement Techniques
-
- Computer Graphics and Visualization Techniques
Papers in
-
- Generative Adversarial Networks and Image Synthesis 2
- Face recognition and analysis 1
-
- Metaheuristic Optimization Algorithms Research 1
- Neural Networks and Applications 1
- Co-authors
- Sepp Hochreiter (4 shared papers)Bernhard Nessler (2 shared papers)Martin Heusel (2 shared papers)Thomas Unterthiner (2 shared papers)Günter Klambauer (2 shared papers)Philipp Seidl (1 shared paper)David P. Kreil (1 shared paper)Michael Kopp (1 shared paper)
- Journals
- International Conference on Learning Representations (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- Austria
In The Last Decade
Hubert Ramsauer
4 papers receiving 2.0k citations
Hubert Ramsauer's Hit Papers
Peers
Comparison fields: 5 of 121
- Computer Vision and Pattern Recognition 1.6k
- Computer Graphics and Computer-Aided Design 208
- Artificial Intelligence 506
- Media Technology 134
- Signal Processing 135
Countries citing papers authored by Hubert Ramsauer
This map shows the geographic impact of Hubert Ramsauer'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 Hubert Ramsauer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hubert Ramsauer more than expected).
Fields of papers citing papers by Hubert Ramsauer
This network shows the impact of papers produced by Hubert Ramsauer. 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 Hubert Ramsauer. The network helps show where Hubert Ramsauer may publish in the future.
Co-authors
The 13 scholars most cited alongside Hubert Ramsauer, 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 | GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium Hit paper breakdown → | 2017 | 1986 |
| 2 | Hopfield Networks is All You Need | 2021 | 77 |
| 3 | Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields | 2018 | 6 |
| 4 | A GAN based solver of black-box inverse problems | 2019 | 1 |
About Hubert Ramsauer
Hubert Ramsauer is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Molecular Biology, Civil and Structural Engineering and Mathematical Physics, having authored 4 papers that have together received 2.1k indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (2 papers), Topology Optimization in Engineering (1 paper), Machine Learning in Bioinformatics (1 paper), COVID-19 diagnosis using AI (1 paper), Metaheuristic Optimization Algorithms Research (1 paper), Face recognition and analysis (1 paper), Neural Networks and Applications (1 paper) and Matrix Theory and Algorithms (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (1.6k citations), Computer Graphics and Computer-Aided Design (208 citations), Artificial Intelligence (506 citations), Media Technology (134 citations) and Signal Processing (135 citations). Hubert Ramsauer has collaborated with scholars based in Austria. Frequent co-authors include Sepp Hochreiter, Bernhard Nessler, Martin Heusel, Thomas Unterthiner, Günter Klambauer, Philipp Seidl, David P. Kreil, Michael Kopp, Michael Widrich and Johannes M. Lehner. Their work appears in journals such as International Conference on Learning Representations and arXiv (Cornell University).
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.