FATE: Feature-Agnostic Transformer-based Encoder for learning generalized embedding spaces in flow cytometry data

Lisa Weijler, Florian Kowarsch, Michael Reiter, Pedro Hermosilla, Margarita Maurer-Granofszky, Michael N. Dworzak. FATE: Feature-Agnostic Transformer-based Encoder for learning generalized embedding spaces in flow cytometry data. In IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2024, Waikoloa, HI, USA, January 3-8, 2024. pages 7941-7949, IEEE, 2024. [doi]

Abstract

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