1 code implementation • 10 Mar 2022 • Yong Zheng Ong, Zuowei Shen, Haizhao Yang
Discretization invariant learning aims at learning in the infinite-dimensional function spaces with the capacity to process heterogeneous discrete representations of functions as inputs and/or outputs of a learning model.
no code implementations • 23 May 2019 • Yong Zheng Ong, Charles K. Chui, Haizhao Yang
This paper introduces a cross adversarial source separation (CASS) framework via autoencoder, a new model that aims at separating an input signal consisting of a mixture of multiple components into individual components defined via adversarial learning and autoencoder fitting.