◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Wouter M. Kouw

Eindhoven University of Technology

12 papers hereh-index 81.2k citations22 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author1
  • first author8
  • middle author2

Across the 11 of 12 papers where every author was matched, so the position is known.

fields
  • stat.ML5
  • cs.LG4
  • cs.CV2
  • cs.CL1
affiliations
  • Eindhoven University of Technology
Homepage
same name
  • Wouter M. Kouw — 22 papers, h 6

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20152020
most citedA review of domain adaptation without target labels

609 citations · 924 across the 12 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.CL2019★ 2 cited

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…

stat.ML2019★ 12 cited

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…

cs.LG2019★ 247 cited

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…

cs.LG2019★ 609 cited

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…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.