RoMAE is a single, drop-in masked autoencoder that utilizes continuous (axial) RoPE to excel in interpolation and representation learning across modalities.

We introduce ChA-MAEViT - a robust, high-performing model that encourages cross-channel interactions for multi-channel imaging.