activity
20102021
most citedUnderstanding Urban Dynamics via Context-aware Tensor Factorization with Neighboring Regularization

75 citations · 129 across the 5 of their papers we have counts for

collaborators

12 papers

physics.geo-ph20212 cited

Construction of Attenuation Relationship of Peak Ground Velocity Using Machine Learning and Examination of Station Correction Factor

Junjie Wu, Yoshihisa Maruyama, Wen Liu

This study tries to develop new attenuation relationships of peak ground velocity using machine learning methods; random forest and neural network. In order to compare with the pre…

hep-ex2020

Measurement of the Born cross sections for at center-of-mass energies between and GeV

BESIII Collaboration, M. Ablikim, M. N. Achasov +487

The Born cross sections for the process at different center-of-mass energies between and GeV are reported with improved precision fro…

cs.LG201975 cited

Understanding Urban Dynamics via Context-aware Tensor Factorization with Neighboring Regularization

Jingyuan Wang, Junjie Wu, Ze Wang +2

Recent years have witnessed the world-wide emergence of mega-metropolises with incredibly huge populations. Understanding residents mobility patterns, or urban dynamics, thus becom…

cs.LG20191 cited

SVM-based Deep Stacking Networks

Jingyuan Wang, Kai Feng, Junjie Wu

The deep network model, with the majority built on neural networks, has been proved to be a powerful framework to represent complex data for high performance machine learning. In r…

cs.SI2018

Inferring Metapopulation Propagation Network for Intra-city Epidemic Control and Prevention

Jingyuan Wang, Xiaojian Wang, Junjie Wu

Since the 21st century, the global outbreaks of infectious diseases such as SARS in 2003, H1N1 in 2009, and H7N9 in 2013, have become the critical threat to the public health and a…

cs.LG2018

Multilevel Wavelet Decomposition Network for Interpretable Time Series Analysis

Jingyuan Wang, Ze Wang, Jianfeng Li +1

Recent years have witnessed the unprecedented rising of time series from almost all kindes of academic and industrial fields. Various types of deep neural network models have been…