activity
20232026
most citedRoot-KGD: A Novel Framework for Root Cause Diagnosis Based on Knowledge Graph and Industrial Data

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

HAD: Heterogeneity-Aware Distillation for Lifelong Heterogeneous Learning

Xuerui Zhang, Xuehao Wang, Zhan Zhuang +5

Lifelong learning aims to preserve knowledge acquired from previous tasks while incorporating knowledge from a sequence of new tasks. However, most prior work explores only streams…

cs.LG2024

Causality-driven Sequence Segmentation for Enhancing Multiphase Industrial Process Data Analysis and Soft Sensing

Yimeng He, Le Yao, Xinmin Zhang +2

The dynamic characteristics of multiphase industrial processes present significant challenges in the field of industrial big data modeling. Traditional soft sensing models frequent…

cs.LG2024

Rethinking the Diffusion Models for Numerical Tabular Data Imputation from the Perspective of Wasserstein Gradient Flow

Zhichao Chen, Haoxuan Li, Fangyikang Wang +5

Diffusion models (DMs) have gained attention in Missing Data Imputation (MDI), but there remain two long-neglected issues to be addressed: (1). Inaccurate Imputation, which arises…

cs.AI20241 cited

Root-KGD: A Novel Framework for Root Cause Diagnosis Based on Knowledge Graph and Industrial Data

Jiyu Chen, Jinchuan Qian, Xinmin Zhang +1

With the development of intelligent manufacturing and the increasing complexity of industrial production, root cause diagnosis has gradually become an important research direction…

cs.LG2023

ABIGX: A Unified Framework for eXplainable Fault Detection and Classification

Yue Zhuo, Jinchuan Qian, Zhihuan Song +1

For explainable fault detection and classification (FDC), this paper proposes a unified framework, ABIGX (Adversarial fault reconstruction-Based Integrated Gradient eXplanation). A…