Vincent Fortuin

664 total citations
18 papers, 128 citations indexed

About

Vincent Fortuin is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Vincent Fortuin has authored 18 papers receiving a total of 128 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 5 papers in Signal Processing and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Vincent Fortuin's work include Gaussian Processes and Bayesian Inference (9 papers), Machine Learning in Healthcare (5 papers) and Time Series Analysis and Forecasting (4 papers). Vincent Fortuin is often cited by papers focused on Gaussian Processes and Bayesian Inference (9 papers), Machine Learning in Healthcare (5 papers) and Time Series Analysis and Forecasting (4 papers). Vincent Fortuin collaborates with scholars based in Switzerland, United Kingdom and United States. Vincent Fortuin's co-authors include Gunnar Rätsch, Stephan Mandt, Richard E. Turner, Ryan Cotterell, Adrià Garriga-Alonso, Heiko Strathmann, Matthias Hüser, Katja Hofmann, Francesco Locatello and Martin Faltys and has published in prestigious journals such as PLoS ONE, IEEE Access and PLoS Computational Biology.

In The Last Decade

Vincent Fortuin

16 papers receiving 125 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Vincent Fortuin Switzerland	6	92	17	17	12	9	18	128
Sanjay Kumar Sonbhadra India	5	99 1.1×	23 1.4×	8 0.5×	23 1.9×	18 2.0×	16	159
Rafid Mahmood Canada	9	34 0.4×	7 0.4×	4 0.2×	5 0.4×	13 1.4×	16	142
Bojian Hou United States	8	136 1.5×	37 2.2×	5 0.3×	5 0.4×	14 1.6×	29	220
Abdullah M. Albarrak Saudi Arabia	7	71 0.8×	26 1.5×	8 0.5×	4 0.3×	26 2.9×	22	194
Nihad Karim Chowdhury Bangladesh	7	68 0.7×	40 2.4×	7 0.4×	7 0.6×	22 2.4×	10	198
B. Uma Maheswari India	7	43 0.5×	44 2.6×	3 0.2×	11 0.9×	9 1.0×	36	146
Devansh Shah India	4	153 1.7×	9 0.5×	10 0.6×	5 0.4×	3 0.3×	8	360
Liam Li	2	65 0.7×	30 1.8×	2 0.1×	8 0.7×	8 0.9×	3	127
Sujatha Canavoy Narahari India	8	55 0.6×	47 2.8×	4 0.2×	14 1.2×	7 0.8×	27	192

Countries citing papers authored by Vincent Fortuin

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Vincent Fortuin

This figure shows the co-authorship network connecting the top 25 collaborators of Vincent Fortuin. A scholar is included among the top collaborators of Vincent Fortuin 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 Vincent Fortuin. Vincent Fortuin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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18 of 18 papers shown

Delacroix, Sylvie, Diana Robinson, Umang Bhatt, et al.. (2025). Beyond Quantification: Navigating Uncertainty in Professional AI Systems. Research Portal (King's College London). 1(1).

Piraud, Marie, Stefan Kesselheim, Vincent Fortuin, et al.. (2025). OneProt: Towards multi-modal protein foundation models via latent space alignment of sequence, structure, binding sites and text encoders. PLoS Computational Biology. 21(11). e1013679–e1013679.

Fortuin, Vincent, et al.. (2022). Probing as Quantifying Inductive Bias. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 1839–1851. 8 indexed citations

Fortuin, Vincent. (2022). Priors in Bayesian Deep Learning: A Review. International Statistical Review. 90(3). 563–591. 48 indexed citations

Fortuin, Vincent, et al.. (2021). MGP-AttTCN: An interpretable machine learning model for the prediction of sepsis. PLoS ONE. 16(5). e0251248–e0251248. 25 indexed citations

Fortuin, Vincent, et al.. (2021). Sparse Gaussian Processes on Discrete Domains. IEEE Access. 9. 76750–76758. 3 indexed citations

Fortuin, Vincent. (2021). Priors in Bayesian Deep Learning: A Review. arXiv (Cornell University). 2 indexed citations

Hüser, Matthias, et al.. (2021). T-DPSOM. 236–245. 5 indexed citations

Fortuin, Vincent, Adrià Garriga-Alonso, Mark van der Wilk, & Laurence Aitchison. (2021). BNNpriors: A library for Bayesian neural network inference with different prior distributions. Software Impacts. 9. 100079–100079. 4 indexed citations

10.

Garriga-Alonso, Adrià & Vincent Fortuin. (2021). Exact Langevin Dynamics with Stochastic Gradients. arXiv (Cornell University). 1 indexed citations

11.

Fortuin, Vincent, et al.. (2020). Conservative Uncertainty Estimation By Fitting Prior Networks. International Conference on Learning Representations. 7 indexed citations

12.

Fortuin, Vincent, et al.. (2020). Sparse Gaussian Process Variational Autoencoders. arXiv (Cornell University). 3511–3519. 2 indexed citations

13.

Fortuin, Vincent & Gunnar Rätsch. (2019). Deep Mean Functions for Meta-Learning in Gaussian Processes.. 3 indexed citations

14.

Fortuin, Vincent, Gunnar Rätsch, & Stephan Mandt. (2019). Multivariate Time Series Imputation with Variational Autoencoders. 9 indexed citations

15.

Hüser, Matthias, et al.. (2019). Variational pSOM: Deep Probabilistic Clustering with Self-Organizing Maps. 1 indexed citations

16.

Georgiou, Andreas, Vincent Fortuin, Harun Mustafa, & Gunnar Rätsch. (2019). Deep Multiple Instance Learning for Taxonomic Classification of Metagenomic read sets. 1 indexed citations

17.

Fortuin, Vincent, Matthias Hüser, Francesco Locatello, Heiko Strathmann, & Gunnar Rätsch. (2018). Deep Self-Organization: Interpretable Discrete Representation Learning on Time Series. 6 indexed citations

18.

Fortuin, Vincent, et al.. (2018). InspireMe: Learning Sequence Models for Stories. Proceedings of the AAAI Conference on Artificial Intelligence. 32(1). 3 indexed citations

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.

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