10 citations · 20 across the 7 of their papers we have counts for
7 papers
An Efficient Transformer for Simultaneous Learning of BEV and Lane Representations in 3D Lane Detection
Ziye Chen, Kate Smith-Miles, Bo Du +2
Accurately detecting lane lines in 3D space is crucial for autonomous driving. Existing methods usually first transform image-view features into bird-eye-view (BEV) by aid of inver…
variable selection and missing data imputation in categorical genomic data analysis by integrated ridge regression and random forest
Siru Wang, Guoqi Qian
Genomic data arising from a genome-wide association study (GWAS) are often not only of large-scale, but also incomplete. A specific form of their incompleteness is missing values w…
The Framework for the Prediction of the Critical Turning Period for Outbreak of COVID-19 Spread in China based on the iSEIR Model
George Xianzhi Yuan, Lan Di, Yudi Gu +2
The goal of this study is to establish a general framework for predicting the so-called critical Turning Period in an infectious disease epidemic such as the COVID-19 outbreak in C…
A Dynamic Epidemic Model for Rumor Spread in Multiplex Network with Numerical Analysis
Lan Di, Yudi Gu, Guoqi Qian +1
This paper focuses on studying and understanding of stochastic dynamics in population composition when the population is subject to rumor spreading. We undertake the study by first…
Bayesian Sparse Global-Local Shrinkage Regression for Selection of Grouped Variables
Zemei Xu, Daniel F. Schmidt, Enes Makalic +2
Most estimates for penalised linear regression can be viewed as posterior modes for an appropriate choice of prior distribution. Bayesian shrinkage methods, particularly the horses…
Parsimonious and powerful composite likelihood testing for group difference and genotype-phenotype association
Zhendong Huang, Davide Ferrari, Guoqi Qian
Testing the association between a phenotype and many genetic variants from case-control data is essential in genome-wide association study (GWAS). This is a challenging task as man…
Parsimonious and Efficient Likelihood Composition by Gibbs Sampling
Davide Ferrari, Guoqi Qian
The traditional maximum likelihood estimator (MLE) is often of limited use in complex high-dimensional data due to the intractability of the underlying likelihood function. Maximum…