Vincent Fortuin
Impact in
- Artificial Intelligence top 10%
- Machine Learning in Healthcare
- Gaussian Processes and Bayesian Inference
- Anomaly Detection Techniques and Applications
- Domain Adaptation and Few-Shot Learning
- Neural Networks and Applications
Papers in
-
- Gaussian Processes and Bayesian Inference 9
- Machine Learning in Healthcare 5
- Bayesian Methods and Mixture Models 3
- Anomaly Detection Techniques and Applications 2
- Topic Modeling 2
-
- Time Series Analysis and Forecasting 4
- Co-authors
- Gunnar Rätsch (7 shared papers)Stephan Mandt (1 shared paper)Richard E. Turner (2 shared papers)Matthias Hüser (3 shared papers)Adrià Garriga-Alonso (2 shared papers)Ryan Cotterell (1 shared paper)Heiko Strathmann (2 shared papers)Katja Hofmann (1 shared paper)
- Journals
- PLoS Computational Biology (1 paper)IEEE Access (1 paper)International Statistical Review (1 paper)PLoS ONE (1 paper)Software Impacts (1 paper)
- Partner nations
- SwitzerlandUnited KingdomUnited States
In The Last Decade
Vincent Fortuin
16 papers receiving 125 citations
Peers
Comparison fields: 5 of 64
- Computational Mathematics 2
- Artificial Intelligence 92
- Statistics, Probability and Uncertainty 8
- Statistics and Probability 8
- Family Practice 2
Countries citing papers authored by Vincent Fortuin
This map shows the geographic impact of Vincent Fortuin'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 Vincent Fortuin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vincent Fortuin more than expected).
Fields of papers citing papers by Vincent Fortuin
This network shows the impact of papers produced by Vincent Fortuin. 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 Vincent Fortuin. The network helps show where Vincent Fortuin may publish in the future.
Co-authors
The 25 scholars most cited alongside Vincent Fortuin, 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 | 2022 | 48 | |
| 2 | 2021 | 25 | |
| 3 | Multivariate Time Series Imputation with Variational Autoencoders | 2019 | 9 |
| 4 | 2022 | 8 | |
| 5 | Conservative Uncertainty Estimation By Fitting Prior Networks | 2020 | 7 |
| 6 | Deep Self-Organization: Interpretable Discrete Representation Learning on Time Series | 2018 | 6 |
| 7 | 2021 | 5 | |
| 8 | 2021 | 4 | |
| 9 | Deep Mean Functions for Meta-Learning in Gaussian Processes. | 2019 | 3 |
| 10 | 2021 | 3 | |
| 11 | 2018 | 3 | |
| 12 | 2021 | 2 | |
| 13 | 2020 | 2 | |
| 14 | Deep Multiple Instance Learning for Taxonomic Classification of Metagenomic read sets | 2019 | 1 |
| 15 | Variational pSOM: Deep Probabilistic Clustering with Self-Organizing Maps | 2019 | 1 |
| 16 | 2021 | 1 | |
| 17 | 2025 | 0 | |
| 18 | 2025 | 0 |
About Vincent Fortuin
Vincent Fortuin is a scholar working on Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Statistics and Probability and Molecular Biology, having authored 18 papers that have together received 128 indexed citations. Recurring topics across this work include Gaussian Processes and Bayesian Inference (9 papers), Machine Learning in Healthcare (5 papers), Time Series Analysis and Forecasting (4 papers), Bayesian Methods and Mixture Models (3 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Anomaly Detection Techniques and Applications (2 papers), Topic Modeling (2 papers) and Advanced Multi-Objective Optimization Algorithms (1 paper). The work is most often cited by research in Computational Mathematics (2 citations), Artificial Intelligence (92 citations), Statistics, Probability and Uncertainty (8 citations), Statistics and Probability (8 citations) and Family Practice (2 citations). Vincent Fortuin has collaborated with scholars based in Switzerland, United Kingdom and United States. Frequent co-authors include Gunnar Rätsch, Stephan Mandt, Richard E. Turner, Matthias Hüser, Adrià Garriga-Alonso, Ryan Cotterell, Heiko Strathmann, Katja Hofmann, Mark van der Wilk and Diana Wotruba. Their work appears in journals such as PLoS Computational Biology, IEEE Access, International Statistical Review, PLoS ONE and Software Impacts.
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.