Out of Distribution Generalization via Interventional Style Transfer in Single-Cell Microscopy

doi:doi:10.57702/tcs1bfj8

Out of Distribution Generalization via Interventional Style Transfer in Single-Cell Microscopy

Real-world deployment of computer vision systems, including in the discovery processes of biomedical research, requires causal representations that are invariant to contextual nuisances and generalize to new data.

BibTex:

@dataset{Wolfgang_M_Pernice_and_Michael_Doron_and_Alex_Quach_and_Aditya_Pratapa_and_Sultan_Kenjeyev_and_Nicholas_De_Veaux_and_Michio_Hirano_and_Juan_C_Caicedo_2025,
    abstract = {Real-world deployment of computer vision systems, including in the discovery processes of biomedical research, requires causal representations that are invariant to contextual nuisances and generalize to new data.},
    author = {Wolfgang M. Pernice and Michael Doron and Alex Quach and Aditya Pratapa and Sultan Kenjeyev and Nicholas De Veaux and Michio Hirano and Juan C. Caicedo},
    doi = {10.57702/tcs1bfj8},
    institution = {No Organization},
    keyword = {'causal representation learning', 'interventional style transfer', 'out-of-distribution generalization', 'single-cell microscopy'},
    month = {jan},
    publisher = {TIB},
    title = {Out of Distribution Generalization via Interventional Style Transfer in Single-Cell Microscopy},
    url = {https://service.tib.eu/ldmservice/dataset/out-of-distribution-generalization-via-interventional-style-transfer-in-single-cell-microscopy},
    year = {2025}
}