Brice Wang

multiVIB: A unified probabilistic contrastive learning framework for atlas-scale integration of single-cell multi-omics data

multiVIB integrates single-cell multi-omics data across modalities and species with a probabilistic contrastive learning framework, achieving state-of-the-art performance while preserving biological variation.

Robust self-supervised denoising of voltage imaging data using CellMincer

CellMincer is a self-supervised deep learning method for denoising voltage imaging data, achieving significant noise reduction and improved functional phenotype separation.