6 papers
SSH-Net: A Deep Neural Network for Predicting Failure Time Distribution Functions under Competing Risks with Application to GPU Data
Jie Min, Yueyao Wang, Mengkun Chen
Competing risks are commonly observed in engineering fields and can bring challenges to time-to-event data modeling when the application scenarios are complicated. Recently, deep n…
What Quality Engineers Need to Know about Degradation Models
Jared M. Clark, Jie Min, Mingyang Li +5
Degradation models play a critical role in quality engineering by enabling the assessment and prediction of system reliability based on data. The objective of this paper is to prov…
Modeling Spatially Correlated Failure-time Data Under Two Distance Functions with an Application to Titan GPU Data
Jared M. Clark, Jie Min, Yueyao Wang +2
One common approach to statistical analysis of spatially correlated data relies on defining a correlation structure based solely on unknown parameters and the physical distance bet…
Performance Evaluation of Large Language Models in Statistical Programming
Xinyi Song, Kexin Xie, Lina Lee +10
The programming capabilities of large language models (LLMs) have revolutionized automatic code generation and opened new avenues for automatic statistical analysis. However, the v…
Bridging the Data Gap in AI Reliability Research and Establishing DR-AIR, a Comprehensive Data Repository for AI Reliability
Simin Zheng, Jared M. Clark, Fatemeh Salboukh +10
Artificial intelligence (AI) technology and systems have been advancing rapidly. However, ensuring the reliability of these systems is crucial for fostering public confidence in th…
Applied Statistics in the Era of Artificial Intelligence: A Review and Vision
Jie Min, Xinyi Song, Simin Zheng +3
The advent of artificial intelligence (AI) technologies has significantly changed many domains, including applied statistics. This review and vision paper explores the evolving rol…