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20242026
most citedDiff-MTS: Temporal-Augmented Conditional Diffusion-based AIGC for Industrial Time Series Towards the Large Model Era

52 citations · 53 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2026

Physics-informed Diffusion Generative Model for Time-Series Data Synthesis in Dynamic Systems

Haiteng Wang, Yunfei Zhu, Tao Wang +4

Industrial time-series signals, such as turbine temperature and rotational speed in aero-engines, are essential for monitoring the health and operational status of complex dynamica…

cs.LG2026

TS-MLLM: A Multi-Modal Large Language Model-based Framework for Industrial Time-Series Big Data Analysis

Haiteng Wang, Yikang Li, Yunfei Zhu +3

Accurate analysis of industrial time-series big data is critical for the Prognostics and Health Management (PHM) of industrial equipment. While recent advancements in Large Languag…

cs.SE2025

GenAI for Simulation Model in Model-Based Systems Engineering

Lin Zhang, Yuteng Zhang, Dusit Niyato +6

Generative AI (GenAI) has demonstrated remarkable capabilities in code generation, and its integration into complex product modeling and simulation code generation can significantl…

cs.LG2024★ 52 cited

Diff-MTS: Temporal-Augmented Conditional Diffusion-based AIGC for Industrial Time Series Towards the Large Model Era

Lei Ren, Haiteng Wang, Yuanjun Laili

Industrial Multivariate Time Series (MTS) is a critical view of the industrial field for people to understand the state of machines. However, due to data collection difficulty and…

cs.LG2024★ 1 cited

AIGC for Industrial Time Series: From Deep Generative Models to Large Generative Models

Lei Ren, Haiteng Wang, Jinwang Li +2

With the remarkable success of generative models like ChatGPT, Artificial Intelligence Generated Content (AIGC) is undergoing explosive development. Not limited to text and images,…