PerturbedVAE disentangles perturbation-specific signals from invariant gene expression structure to recover causal representations and improve out-of-distribution prediction in single-cell perturbation modeling.
arXiv preprint arXiv:2506.12439 , year=
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Proposes CITE-VAE, a latent dynamical causal VAE with identifiability analysis for single-cell perturbation prediction, claiming better OOD generalization on CRISPR data.
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What Makes a Representation Good for Single-Cell Perturbation Prediction?
PerturbedVAE disentangles perturbation-specific signals from invariant gene expression structure to recover causal representations and improve out-of-distribution prediction in single-cell perturbation modeling.
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Learning Latent Dynamical Causal Processes for Single-Cell Perturbation Prediction
Proposes CITE-VAE, a latent dynamical causal VAE with identifiability analysis for single-cell perturbation prediction, claiming better OOD generalization on CRISPR data.