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Cell DISentangled Experts for Covariate counTerfactuals (CellDISECT). Causal generative model designed to disentangle known covariate variations from unknown ones at test time while simultaneously lea
pip install celldisect
PyPI declares 37 unique dependency rules for this release. Environment markers are shown when supplied by the project.
<0.43,>=0.42<0.10.9,>=0.10.8<1.0.0,>=0.20.3<2.3.0,>=2.1.0<1.27.0,>=1.26.3<0.4.24,>=0.4.16<0.4.24,>=0.4.16<2.3.0,>=2.2.0<0.6.0,>=0.5.1<1.2.0,>=1.1.5<2.10.0,>=2.9.0<1.13.0,>=1.12.0The compact report shows 18 of 37 declarations. The interactive dependency graph loads the complete metadata.
celldisect publishes 1 wheel and 1 source archive for version 0.1.6. Wheel platform tags: any.
Declared Python classifiers: 3.10, 3.9.
PyPI lists 8 releases with files. The first dated release is ; 3 releases fall within the 365 days preceding the latest dated release. The current release files were uploaded on . The preceding dated release was .