A generative framework using latent heteroscedastic Gaussian process approximated via Hilbert space methods plus optimal transport to model population trends and infer trajectories in temporal scRNA-seq data.
Nature Machine Intelligence , volume=
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Modeling Temporal scRNA-seq Data with Latent Gaussian Process and Optimal Transport
A generative framework using latent heteroscedastic Gaussian process approximated via Hilbert space methods plus optimal transport to model population trends and infer trajectories in temporal scRNA-seq data.