Publications

Input-Output Analysis : Foundations and Extensions

This edition of Ronald Miller and Peter Blair's classic textbook is an essential reference for students and scholars in the input-output research and applications community. The...

Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China

DeepLabCut: markerless pose estimation of user-defined body parts with deep learning

Physics-informed machine learning

GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database

Abstract Summary The Genome Taxonomy Database Toolkit (GTDB-Tk) provides objective taxonomic assignments for bacterial and archaeal genomes based on the GTDB. GTDB-Tk is computa...

Presumed Asymptomatic Carrier Transmission of COVID-19

This study describes possible transmission of novel coronavirus disease 2019 (COVID-19) from an asymptomatic Wuhan resident to 5 family members in Anyang, a Chinese city in the ...

OpenPose: Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields

Realtime multi-person 2D pose estimation is a key component in enabling machines to have an understanding of people in images and videos. In this work, we present a realtime app...

Temporal dynamics in viral shedding and transmissibility of COVID-19

We report temporal patterns of viral shedding in 94 patients with laboratory-confirmed COVID-19 and modeled COVID-19 infectiousness profiles from a separate sample of 77 infecto...

Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition

Dynamics of human body skeletons convey significant information for human action recognition. Conventional approaches for modeling skeletons usually rely on hand-crafted parts o...

Imbalanced Host Response to SARS-CoV-2 Drives Development of COVID-19

Graphene-Like Two-Dimensional Materials

ADVERTISEMENT RETURN TO ISSUEPREVReviewNEXTGraphene-Like Two-Dimensional MaterialsMingsheng Xu*, Tao Liang, Minmin Shi, and Hongzheng ChenView Author Information State Key Labor...

CutMix: Regularization Strategy to Train Strong Classifiers With Localizable Features

Regional dropout strategies have been proposed to enhance performance of convolutional neural network classifiers. They have proved to be effective for guiding the model to atte...