RPN: Reconciled Polynomial Network
This paper proposes the task of "deep function learning" and introduce a novel deep function learning base model,
i.e., the Reconciled Polynomial Network (RPN).
RPN has a versatile model architecture and attains superior modeling capabilities for diverse deep function
learning tasks on various multi-modality datasets.
RPN also provides a canonical representation for many existing machine learning and deep learning models,
including but not limited to PGMs, kernel SVM, MLP and KAN.