Rotation Invariance for Unsupervised Cell Representation Learning - Analysis of The Impact of Enforcing Rotation Invariance or Equivariance on Representation for Cell Classification. - Philipp Gräbel; Ina Laube; Martina Crysandt; Reinhild Herwartz; Melanie Baumann; Barbara Mara Klinkhammer; Peter Boor; Tim H. Brümmendorf; Dorit Merhof (Bildverarbeitung für die Medizin, 2021)

Surrounding Cell Suppression For Unsupervised Representation Learning In Hematological Cell Classification. - Philipp Gräbel; Ina Laube; Martina Crysandt; Reinhild Herwartz; Melanie Baumann; Barbara Mara Klinkhammer; Peter Boor; Tim H. Brümmendorf; Dorit Merhof (ISBI, 2021)

Linear Discriminant Analysis Metric Learning Using Siamese Neural Networks. - Abin Jose; Qi Mei; Dennis Eschweiler; Ina Laube; Johannes Stegmaier (ICIP, 2022)

End-to-End Classification of Cell-Cycle Stages with Center-Cell Focus Tracker Using Recurrent Neural Networks. - Abin Jose; Rijo Roy; Dennis Eschweiler; Ina Laube; Reza Azad; Daniel Moreno-Andrés; Johannes Stegmaier (ICASSP, 2023)

Unsupervised Learning for Feature Extraction and Temporal Alignment of 3D+t Point Clouds of Zebrafish Embryos. - Zhu Chen 002; Ina Laube; Johannes Stegmaier (MICCAI (8), 2023)

Denoising diffusion probabilistic models for generation of realistic fully-annotated microscopy image datasets. - Dennis Eschweiler; Rüveyda Yilmaz; Matisse Baumann; Ina Laube; Rijo Roy; Abin Jose; Daniel Brückner; Johannes Stegmaier (PLoS Comput. Biol., 2024)