Cover Image

Graph Autoencoder for Process Monitoring

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Zhang, Xiangrui
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Product-Aware Deep Autoencoders for Robust Process Monitoring in Multi-Product Cyber-Physical Systems
by: Islam, MD Shafikul, et al.
Published: (2026)

Directly Follows Graphs Go Predictive Process Monitoring With Graph Neural Networks
by: Lischka, Attila, et al.
Published: (2025)

Revisiting Graph Autoencoders as Implicit Contrastive Learners
by: Li, Jintang, et al.
Published: (2024)

Predictive Process Monitoring Using Object-centric Graph Embeddings
by: Gherissi, Wissam, et al.
Published: (2025)

UGMAE: A Unified Framework for Graph Masked Autoencoders
by: Tian, Yijun, et al.
Published: (2024)

Generalized Graph Transformer Variational Autoencoder
by: Karki, Siddhant
Published: (2025)

Federated Sequence-to-Sequence Learning for Load Disaggregation from Unbalanced Low-Resolution Smart Meter Data
by: Li, Xiangrui
Published: (2024)

Autoencoding Conditional Neural Processes for Representation Learning
by: Prokhorov, Victor, et al.
Published: (2023)

GraphCroc: Cross-Correlation Autoencoder for Graph Structural Reconstruction
by: Duan, Shijin, et al.
Published: (2024)

Disentangled Graph Autoencoder for Treatment Effect Estimation
by: Fan, Di, et al.
Published: (2024)

T-GAE: Transferable Graph Autoencoder for Network Alignment
by: He, Jiashu, et al.
Published: (2023)

IMPA-HGAE:Intra-Meta-Path Augmented Heterogeneous Graph Autoencoder
by: Lin, Di, et al.
Published: (2025)

Anomaly Correction of Business Processes Using Transformer Autoencoder
by: Gong, Ziyou, et al.
Published: (2024)

Pre-Training Graph Contrastive Masked Autoencoders are Strong Distillers for EEG
by: Wei, Xinxu, et al.
Published: (2024)

Graph-Regularized Sparse Autoencoders for LLM Safety Steering
by: Yeon, Jehyeok, et al.
Published: (2025)

Enhancing Fairness in Autoencoders for Node-Level Graph Anomaly Detection
by: Wang, Shouju, et al.
Published: (2025)

Preserving Node Distinctness in Graph Autoencoders via Similarity Distillation
by: Chen, Ge, et al.
Published: (2024)

Generating Realistic Adversarial Examples for Business Processes using Variational Autoencoders
by: Stevens, Alexander, et al.
Published: (2024)

GraViti: Graph-Level Variational Autoencoders with Relaxed Permutation Invariance
by: Bresson, Roman, et al.
Published: (2026)

Variational Autoencoder-Based Approach to Latent Feature Analysis on Efficient Representation of Power Load Monitoring Data
by: Xie, Boyu, et al.
Published: (2025)

Symmetry-Aware Graph Metanetwork Autoencoders: Model Merging through Parameter Canonicalization
by: Boufalis, Odysseas, et al.
Published: (2025)

MoRE-GNN: Multi-omics Data Integration with a Heterogeneous Graph Autoencoder
by: Wang, Zhiyu, et al.
Published: (2025)

GRASPED: Graph Anomaly Detection using Autoencoder with Spectral Encoder and Decoder (Full Version)
by: Choong, Wei Herng, et al.
Published: (2025)

Node Level Graph Autoencoder: Unified Pretraining for Textual Graph Learning
by: Hu, Wenbin, et al.
Published: (2024)

Improving Sparse Autoencoder with Dynamic Attention
by: Wang, Dongsheng, et al.
Published: (2026)

mRNA2vec: mRNA Embedding with Language Model in the 5'UTR-CDS for mRNA Design
by: Zhang, Honggen, et al.
Published: (2024)

Condition Monitoring with Incomplete Data: An Integrated Variational Autoencoder and Distance Metric Framework
by: Ahang, Maryam, et al.
Published: (2024)

Masked Graph Autoencoders with Contrastive Augmentation for Spatially Resolved Transcriptomics Data
by: Fang, Donghai, et al.
Published: (2024)

A Simplex Witness Certificate for Constant Collapse in Variational Autoencoders
by: Zhang, Zegu, et al.
Published: (2026)

Manifold-Matching Autoencoders
by: Cheret, Laurent, et al.
Published: (2026)

Bidirectional Variational Autoencoders
by: Kosko, Bart, et al.
Published: (2025)

Sparse Autoencoders, Again?
by: Lu, Yin, et al.
Published: (2025)

Autoencoding Random Forests
by: Vu, Binh Duc, et al.
Published: (2025)

Revealing the Power of Masked Autoencoders in Traffic Forecasting
by: Sun, Jiarui, et al.
Published: (2023)

AutoGraphAD: Unsupervised network anomaly detection using Variational Graph Autoencoders
by: Anyfantis, Georgios, et al.
Published: (2025)

Are Sparse Autoencoder Benchmarks Reliable?
by: Chanin, David
Published: (2026)

Hellinger Multimodal Variational Autoencoders
by: Vo, Huyen, et al.
Published: (2026)

Autoencoders for Anomaly Detection are Unreliable
by: Bouman, Roel, et al.
Published: (2025)

Prescriptive Process Monitoring Under Resource Constraints: A Reinforcement Learning Approach
by: Shoush, Mahmoud, et al.
Published: (2023)

DeepFilter: A Transformer-style Framework for Accurate and Efficient Process Monitoring
by: Wang, Hao, et al.
Published: (2025)