GPO-VAE reinterprets a VAE's perturbation parameters as a gene-by-gene causal matrix, trains it with a differential-expression-matching loss, and reports state-of-the-art perturbation prediction plus GRN inference on three Perturb-seq datasets.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
GPO-VAE: Modeling Explainable Gene Perturbation Responses utilizing GRN-Aligned Parameter Optimization
GPO-VAE reinterprets a VAE's perturbation parameters as a gene-by-gene causal matrix, trains it with a differential-expression-matching loss, and reports state-of-the-art perturbation prediction plus GRN inference on three Perturb-seq datasets.