Stephan Mandt
Impact in
- Computational Mathematics top 5%
- Artificial Intelligence top 2%
- Anomaly Detection Techniques and Applications
- Gaussian Processes and Bayesian Inference
Papers in
-
- Gaussian Processes and Bayesian Inference 8
- Anomaly Detection Techniques and Applications 4
- Machine Learning and Algorithms 4
-
- Generative Adversarial Networks and Image Synthesis 10
- Image and Signal Denoising Methods 5
- Advanced Data Compression Techniques 4
- Co-authors
- Cheng Zhang (4 shared papers)Hedvig Kjellström (2 shared papers)Judith Bütepage (1 shared paper)David M. Blei (5 shared papers)Matthew D. Hoffman (2 shared papers)Achim Rosch (4 shared papers)Robert Bamler (10 shared papers)Marius Kloft (8 shared papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (3 papers)Machine Learning (3 papers)Physical Review Letters (2 papers)Scientific Reports (2 papers)Physical Review A (2 papers)
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Stephan Mandt
56 papers receiving 1.6k citations
Stephan Mandt's Hit Papers
Peers
Comparison fields: 5 of 140
- Computational Mathematics 19
- Artificial Intelligence 663
- Statistical and Nonlinear Physics 174
- Computer Vision and Pattern Recognition 279
- Atomic and Molecular Physics, and Optics 395
Countries citing papers authored by Stephan Mandt
This map shows the geographic impact of Stephan Mandt'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 Mandt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephan Mandt more than expected).
Fields of papers citing papers by Stephan Mandt
This network shows the impact of papers produced by Stephan Mandt. 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 Mandt. The network helps show where Stephan Mandt may publish in the future.
Co-authors
The 25 scholars most cited alongside Stephan Mandt, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 58 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Advances in Variational Inference Hit paper breakdown → | 2018 | 379 |
| 2 | 2012 | 319 | |
| 3 | 2017 | 167 | |
| 4 | 2019 | 132 | |
| 5 | 2020 | 72 | |
| 6 | 2010 | 59 | |
| 7 | 2022 | 46 | |
| 8 | Dynamic word embeddings | 2017 | 41 |
| 9 | 2023 | 39 | |
| 10 | 2020 | 29 | |
| 11 | 2022 | 28 | |
| 12 | 2022 | 28 | |
| 13 | 2017 | 28 | |
| 14 | 2022 | 26 | |
| 15 | 2019 | 22 | |
| 16 | 2024 | 21 | |
| 17 | 2023 | 20 | |
| 18 | 2011 | 19 | |
| 19 | 2023 | 17 | |
| 20 | 2024 | 14 |
About Stephan Mandt
Stephan Mandt is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Atomic and Molecular Physics, and Optics, Signal Processing and Statistics and Probability, having authored 58 papers that have together received 1.7k indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (10 papers), Gaussian Processes and Bayesian Inference (8 papers), Cold Atom Physics and Bose-Einstein Condensates (6 papers), Image and Signal Denoising Methods (5 papers), Anomaly Detection Techniques and Applications (4 papers), Time Series Analysis and Forecasting (4 papers), Machine Learning and Algorithms (4 papers) and Advanced Data Compression Techniques (4 papers). The work is most often cited by research in Computational Mathematics (19 citations), Artificial Intelligence (663 citations), Statistical and Nonlinear Physics (174 citations), Computer Vision and Pattern Recognition (279 citations) and Atomic and Molecular Physics, and Optics (395 citations). Stephan Mandt has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Cheng Zhang, Hedvig Kjellström, Judith Bütepage, David M. Blei, Matthew D. Hoffman, Achim Rosch, Robert Bamler, Marius Kloft, Robert A. Vandermeulen and Simon Braun. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Machine Learning, Physical Review Letters, Scientific Reports and Physical Review A.
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.