609 citations · 924 across the 12 of their papers we have counts for
12 papers
Online system identification in a Duffing oscillator by free energy minimisation
Wouter M Kouw
Online system identification is the estimation of parameters of a dynamical system, such as mass or friction coefficients, for each measurement of the input and output signals. Her…
The Data Representativeness Criterion: Predicting the Performance of Supervised Classification Based on Data Set Similarity
Evelien Schat, Rens van de Schoot, Wouter M. Kouw +2
In a broad range of fields it may be desirable to reuse a supervised classification algorithm and apply it to a new data set. However, generalization of such an algorithm and thus…
Back to the Future -- Sequential Alignment of Text Representations
Johannes Bjerva, Wouter Kouw, Isabelle Augenstein
Language evolves over time in many ways relevant to natural language processing tasks. For example, recent occurrences of tokens 'BERT' and 'ELMO' in publications refer to neural n…
A cross-center smoothness prior for variational Bayesian brain tissue segmentation
Wouter M. Kouw, Silas N. Ørting, Jens Petersen +2
Suppose one is faced with the challenge of tissue segmentation in MR images, without annotators at their center to provide labeled training data. One option is to go to another med…
An introduction to domain adaptation and transfer learning
Wouter M. Kouw, Marco Loog
In machine learning, if the training data is an unbiased sample of an underlying distribution, then the learned classification function will make accurate predictions for new sampl…
A review of domain adaptation without target labels
Wouter M. Kouw, Marco Loog
Domain adaptation has become a prominent problem setting in machine learning and related fields. This review asks the question: how can a classifier learn from a source domain and…