490 citations · 1.5k across the 56 of their papers we have counts for
6 papers · 1 filter
Physical Knowledge Enhanced Deep Neural Network for Sea Surface Temperature Prediction
Yuxin Meng, Feng Gao, Eric Rigall +3
Traditionally, numerical models have been deployed in oceanography studies to simulate ocean dynamics by representing physical equations. However, many factors pertaining to ocean…
Physics-Guided Generative Adversarial Networks for Sea Subsurface Temperature Prediction
Yuxin Meng, Eric Rigall, Xueen Chen +3
Sea subsurface temperature, an essential component of aquatic wildlife, underwater dynamics and heat transfer with the sea surface, is affected by global warming in climate change.…
Network Embedding via Deep Prediction Model
Xin Sun, Zenghui Song, Yongbo Yu +3
Network-structured data becomes ubiquitous in daily life and is growing at a rapid pace. It presents great challenges to feature engineering due to the high non-linearity and spars…
An Overview on Data Representation Learning: From Traditional Feature Learning to Recent Deep Learning
Guoqiang Zhong, Li-Na Wang, Junyu Dong
Since about 100 years ago, to learn the intrinsic structure of data, many representation learning approaches have been proposed, including both linear ones and nonlinear ones, supe…
Banzhaf Random Forests
Jianyuan Sun, Guoqiang Zhong, Junyu Dong +1
Random forests are a type of ensemble method which makes predictions by combining the results of several independent trees. However, the theory of random forests has long been outp…
A PCA-Based Convolutional Network
Yanhai Gan, Jun Liu, Junyu Dong +1
In this paper, we propose a novel unsupervised deep learning model, called PCA-based Convolutional Network (PCN). The architecture of PCN is composed of several feature extraction…