SoftwareApplication
name: Data underlying the publication/thesis chapter: Learning to Adapt to Position Bias in Vision Transformer Classifiers
description: Data underlying the publication/thesis chapter: Learning to Adapt to Position Bias in Vision Transformer Classifiers
description: This article proposes a novel method to measure learned position bias in Vision Transformers, and investigates which model design choices affect learned equivariance.
code repository: https://data.4tu.nl/v3/datasets/9c507af0-7860-45e7-b9bf-1ff14cdfe4a3.git
author: https://orcid.org/0000-0002-9798-0214
author: https://orcid.org/0000-0002-6913-0482
keywords: position bias
keywords: computer vision
keywords: Vision Transformers
keywords: position embeddings
programming language: C++
programming language: Jupyter Notebook
programming language: Markdown
programming language: Other
programming language: Python
programming language: Shell
programming language: YAML
programming language: large-text-file
license:
  creative work: creativeWork
    name: CC-BY-4.0
reference publication: arxiv.2505.13137

https://orcid.org/0000-0002-9798-0214
type: Person
given name: Robert-Jan
family name: Bruintjes
name: Robert-Jan Bruintjes

https://orcid.org/0000-0002-6913-0482
type: Person
given name: Jan
family name: van Gemert
name: Jan van Gemert

arxiv.2505.13137
type: ScholarlyArticle
name: Learning to Adapt to Position Bias in Vision Transformer Classifiers
url: https://doi.org/10.48550%2Farxiv.2505.13137