This method, known as GenoDrawing, involves training the autoencoder with a large dataset of apple images. The generated embeddings, along with SNP data, are then used to predict and reconstruct ...

Our residual tokens learn high-frequency details, like edges of an object, or a person's hair, eyes, or mouth. These are places where discrete tokens can make mistakes," says Tang.