Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling

1 code implementation • 7 Nov 2022 • Romain Lopez, Nataša Tagasovska, Stephen Ra, Kyunghyn Cho, Jonathan K. Pritchard, Aviv Regev

Instead, recent methods propose to leverage non-stationary data, as well as the sparse mechanism shift assumption in order to learn disentangled representations with a causal semantic.

Disentanglement Domain Generalization +1