GeneICL: A Tabular Foundation Model for Bulk Transcriptomics
GeneICL is a 4.2M-parameter tabular foundation model designed to predict clinical outcomes from bulk gene expression data using in-context learning. It achieves state-of-the-art performance by combining transcriptomics-aware pretraining with an efficient recurrent architecture, significantly outperforming existing models while remaining computationally cheap and fast.