Excited to present our framework for interpretable disentanglement in multi condition data at ICML' 26 arxiv.org/abs/2506.17182 . While useful for different types of data, we think it's particularly useful if you have omics collected across distinct covariates like age or perturbations! Try it out!
Disentangled representations enable models to separate factors of variation that are shared across experimental conditions from those that are condition-specific. This separation is essential in domai...
