This paper proposes a novel deep learning framework based on integral autoencoders (IAE-Net) for discretization invariant learning. The ba- sic building block ...

Mar 10, 2022 · This paper proposes a novel deep learning framework based on integral autoencoders (IAE-Net) for discretization invariant learning. The basic ...

Jan 1, 2022 · IAE-Net is trained with randomized data augmentation that generates training data with heterogeneous structures to facilitate the performance of ...

Sep 6, 2022 · This paper proposes a novel deep learning framework based on integral autoencoders (IAE-Net) for discretization invariant learning. The ...

IAE-Net: Integral Autoencoders for Discretization-Invariant Learning ... This repository contains the code used for the implementation of the paper: IAE-Net: ...

Mar 8, 2022 · IAE-Net is trained with randomized data augmentation that generates training data with heterogeneous structures to facilitate the performance of ...

Integral autoencoder network for discretization-invariant learning. YZ Ong, Z Shen, H Yang. Journal of Machine Learning Research 23 (286), 1-45, 2022. 12, 2022.

AutoEncoder. Integral autoencoder network for discretization-invariant learning. JMLR, 2022. paper. Yong Zheng Ong, Zuowei Shen, and Haizhao Yang. Variational ...

Discretization invariant learning aims at learning in the infinite-dimensional function spaces with the capacity to process heterogeneous discrete ...