Abstract We present a deep-learning framework, CrysXPP, to allow rapid and accurate prediction of electronic, magnetic, elastic properties wide range materials. CrysXPP lowers the need for large property tagged datasets by intelligently designing an autoencoder, CrysAE. The important structural chemical captured CrysAE from amount available crystal graphs data helped in achieving low errors. Mo...