Wouter M. Kouw

1.1k total citations · 1 hit paper
19 papers, 585 citations indexed

About

Wouter M. Kouw is a scholar working on Artificial Intelligence, Control and Systems Engineering and Statistical and Nonlinear Physics. According to data from OpenAlex, Wouter M. Kouw has authored 19 papers receiving a total of 585 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 4 papers in Control and Systems Engineering and 2 papers in Statistical and Nonlinear Physics. Recurrent topics in Wouter M. Kouw's work include Domain Adaptation and Few-Shot Learning (6 papers), Control Systems and Identification (4 papers) and Machine Learning and ELM (3 papers). Wouter M. Kouw is often cited by papers focused on Domain Adaptation and Few-Shot Learning (6 papers), Control Systems and Identification (4 papers) and Machine Learning and ELM (3 papers). Wouter M. Kouw collaborates with scholars based in Netherlands, Denmark and China. Wouter M. Kouw's co-authors include Marco Loog, Adriënne M. Mendrik, Jan Wolff, Jordi Minnema, F. Diblen, Maureen van Eijnatten, Jesse H. Krijthe, Bert de Vries, Duco Veen and Jie Ma and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and Journal of Machine Learning Research.

In The Last Decade

Wouter M. Kouw

17 papers receiving 566 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A Review of Domain Adaptation without Target Labels

2019 374 citations Wouter M. Kouw, Marco Loog IEEE Transactions on Pattern Analysis and Machine Intelligence profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Wouter M. Kouw Netherlands	7	295	166	81	64	39	19	585
Fengxiang He China	16	345 1.2×	572 3.4×	99 1.2×	42 0.7×	29 0.7×	36	997
Shoubhik Debnath United States	5	147 0.5×	320 1.9×	70 0.9×	47 0.7×	30 0.8×	9	699
Stéphane Lathuilière France	12	244 0.8×	369 2.2×	33 0.4×	48 0.8×	35 0.9×	32	643
Binhui Xie China	11	549 1.9×	393 2.4×	83 1.0×	14 0.2×	60 1.5×	12	745
Snehasis Mukherjee India	12	283 1.0×	450 2.7×	91 1.1×	76 1.2×	36 0.9×	43	900
Huiling Lu China	9	291 1.0×	151 0.9×	272 3.4×	59 0.9×	30 0.8×	43	682
Zhuang Liu China	7	183 0.6×	278 1.7×	68 0.8×	36 0.6×	13 0.3×	21	673
Ibrahem Kandel Portugal	9	204 0.7×	201 1.2×	216 2.7×	79 1.2×	17 0.4×	9	710

Countries citing papers authored by Wouter M. Kouw

Since Specialization

Citations

This map shows the geographic impact of Wouter M. Kouw'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 Wouter M. Kouw with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wouter M. Kouw more than expected).

Fields of papers citing papers by Wouter M. Kouw

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wouter M. Kouw. 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 Wouter M. Kouw. The network helps show where Wouter M. Kouw may publish in the future.

Co-authorship network of co-authors of Wouter M. Kouw

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

All Works

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19 of 19 papers shown

Bagaev, Dmitry, et al.. (2026). Gaussian Variational Inference With Non-Gaussian Factors for State Estimation: A UWB Localization Case Study. IEEE Robotics and Automation Letters. 11(3). 2762–2769.

Ma, Jie, et al.. (2024). Bayesian Inference of Collision Avoidance Intent During Ship Encounters. IEEE Transactions on Automation Science and Engineering. 22. 17397–17410. 11 indexed citations

Ma, Jie, et al.. (2024). Multiple Variational Kalman-GRU for Ship Trajectory Prediction With Uncertainty. IEEE Transactions on Aerospace and Electronic Systems. 61(2). 3654–3667. 1 indexed citations

Kouw, Wouter M.. (2023). Information-Seeking Polynomial NARX Model-Predictive Control Through Expected Free Energy Minimization. IEEE Control Systems Letters. 8. 37–42. 1 indexed citations

Kouw, Wouter M., et al.. (2022). Variational message passing for online polynomial NARMAX identification. 2022 American Control Conference (ACC). 2755–2760. 2 indexed citations

Schoukens, Maarten, et al.. (2022). Message Passing-based System Identification for NARMAX Models. 2022 IEEE 61st Conference on Decision and Control (CDC). 6. 7309–7314. 2 indexed citations

Kouw, Wouter M. & Marco Loog. (2021). Robust domain-adaptive discriminant analysis. Pattern Recognition Letters. 148. 107–113.

Kouw, Wouter M., et al.. (2021). Message Passing-Based Inference for Time-Varying Autoregressive Models. Entropy. 23(6). 683–683. 6 indexed citations

Kouw, Wouter M., et al.. (2021). On Epistemics in Expected Free Energy for Linear Gaussian State Space Models. Entropy. 23(12). 1565–1565. 3 indexed citations

10.

Schoot, Rens van de, et al.. (2020). The data representativeness criterion: Predicting the performance of supervised classification based on data set similarity. PLoS ONE. 15(8). e0237009–e0237009. 17 indexed citations

11.

Bjerva, Johannes, Wouter M. Kouw, & Isabelle Augenstein. (2020). Back to the Future – Temporal Adaptation of Text Representations. Proceedings of the AAAI Conference on Artificial Intelligence. 34(5). 7440–7447. 4 indexed citations

12.

Kouw, Wouter M., et al.. (2020). Bayesian joint state and parameter tracking in autoregressive models. TU/e Research Portal. 95–104. 3 indexed citations

13.

Kouw, Wouter M., et al.. (2020). Online Variational Message Passing in Hierarchical Autoregressive Models. TU/e Research Portal. 1337–1342. 4 indexed citations

14.

Kouw, Wouter M., Jesse H. Krijthe, & Marco Loog. (2019). \nRobust Importance-Weighted Cross-Validation Under Sample Selection Bias. Radboud Repository (Radboud University). 1 indexed citations

15.

Kouw, Wouter M., Marco Loog, Lambertus W. Bartels, & Adriënne M. Mendrik. (2019). Learning An Mr Acquisition-Invariant Representation Using Siamese Neural Networks. arXiv (Cornell University). 6 indexed citations

16.

Kouw, Wouter M. & Marco Loog. (2019). A Review of Domain Adaptation without Target Labels. IEEE Transactions on Pattern Analysis and Machine Intelligence. 43(3). 766–785. 374 indexed citations breakdown →

17.

Kouw, Wouter M. & Marco Loog. (2019). A review of single-source unsupervised domain adaptation.. 8 indexed citations

18.

Minnema, Jordi, Maureen van Eijnatten, Wouter M. Kouw, et al.. (2018). CT image segmentation of bone for medical additive manufacturing using a convolutional neural network. Computers in Biology and Medicine. 103. 130–139. 103 indexed citations

19.

Kouw, Wouter M., et al.. (2016). Feature-level domain adaptation. Journal of Machine Learning Research. 17(1). 5943–5974. 39 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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