Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.

Cell-type Annotation for Single-cell Transcriptomics using Deep Learning with a Weighted Graph Neural Network

The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell level. CPA performs OOD predictions of unseen combinations of dr…

Deep probabilistic analysis of single-cell and spatial omics data