Publications (10)
Variable Selection for Multi-Source Count Data with Controlled False Discovery Rate
Shan Tang, Shanjun Mao, Shourong Ma +1
The rapid generation of complex, highly skewed, and zero-inflated multi-source count data poses significant challenges for variable selection, particularly in biomedical domains li…
Asymptotic Distribution-Free Tests for Ultra-high Dimensional Parametric Regressions via Projected Empirical Processes and -value Combination
Falong Tan, Shan Tang, Lixing Zhu
This paper develops a novel methodology for testing the goodness-of-fit of sparse parametric regression models based on projected empirical processes and p-value combination, where…
CM-GAI: Continuum Mechanistic Generative Artificial Intelligence Theory for Data Dynamics
Shan Tang, Ziwei Cao, Zhenling Yang +4
Generative artificial intelligence (GAI) plays a fundamental role in high-impact AI-based systems such as SORA and AlphaFold. Currently, GAI shows limited capability in the special…
LRBmat: A Novel Gut Microbial Interaction and Individual Heterogeneity Inference Method for Colorectal Cancer
Shan Tang, Shanjun Mao, Yangyang Chen +4
Many diseases are considered to be closely related to the changes in the gut microbial community, including colorectal cancer (CRC), which is one of the most common cancers in the…
Hammer: Reviving RowHammer Attacks on New Architectures via Prefetching
Weijie Chen, Shan Tang, Yulin Tang +3
Rowhammer is a critical vulnerability in dynamic random access memory (DRAM) that continues to pose a significant threat to various systems. However, we find that conventional load…
A sequential linear programming (SLP) approach for uncertainty analysis-based data-driven computational mechanics
Mengcheng Huang, Chang Liu, Zongliang Du +2
In this article, an efficient sequential linear programming algorithm (SLP) for uncertainty analysis-based data-driven computational mechanics (UA-DDCM) is presented. By assuming t…
BENCHIP: Benchmarking Intelligence Processors
Jinhua Tao, Zidong Du, Qi Guo +12
The increasing attention on deep learning has tremendously spurred the design of intelligence processing hardware. The variety of emerging intelligence processors requires standard…
STW-MD: A Novel Spatio-Temporal Weighting and Multi-Step Decision Tree Method for Considering Spatial Heterogeneity in Brain Gene Expression Data
Shanjun Mao, Xiao Huang, Runjiu Chen +6
Motivation: Gene expression during brain development or abnormal development is a biological process that is highly dynamic in spatio and temporal. Due to the lack of comprehensive…
Data-driven Topology Optimization (DDTO) for Three-dimensional Continuum Structures
Yunhang Guo, Zongliang Du, Lubin Wang +6
Developing appropriate analytic-function-based constitutive models for new materials with nonlinear mechanical behavior is demanding. For such kinds of materials, it is more challe…
A mechanistic-based data-driven approach to accelerate structural topology optimization through finite element convolutional neural network (FE-CNN)
Tianle Yue, Hang Yang, Zongliang Du +4
In this paper, a mechanistic data-driven approach is proposed to accelerate structural topology optimization, employing an in-house developed finite element convolutional neural ne…