Cover Image

Anomaly Correction of Business Processes Using Transformer Autoencoder

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Gong, Ziyou, Fang, Xianwen, Wu, Ping
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

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

A Real-time Anomaly Detection Using Convolutional Autoencoder with Dynamic Threshold
by: Maitra, Sarit, et al.
Published: (2024)

Leveraging GPT-4o Efficiency for Detecting Rework Anomaly in Business Processes
by: Derakhshan, Mohammad, et al.
Published: (2025)

WEITS: A Wavelet-enhanced residual framework for interpretable time series forecasting
by: Guo, Ziyou, et al.
Published: (2024)

An Innovative Next Activity Prediction Using Process Entropy and Dynamic Attribute-Wise-Transformer in Predictive Business Process Monitoring
by: Zare, Hadi, et al.
Published: (2025)

Deep Autoencoders for Unsupervised Anomaly Detection in Wildfire Prediction
by: Üstek, İrem, et al.
Published: (2024)

PGTNet: A Process Graph Transformer Network for Remaining Time Prediction of Business Process Instances
by: Elyasi, Keyvan Amiri, et al.
Published: (2024)

Graph Autoencoder for Process Monitoring
by: Zhang, Xiangrui
Published: (2026)

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

EEG Artifact Detection and Correction with Deep Autoencoders
by: Aquilué-Llorens, David, et al.
Published: (2025)

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

Multi-scale Masked Autoencoder for Electrocardiogram Anomaly Detection
by: Zhou, Ya, et al.
Published: (2025)

Drift-Aware Variational Autoencoder-based Anomaly Detection with Two-level Ensembling
by: Li, Jin, et al.
Published: (2026)

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

Improving Variational Autoencoder using Random Fourier Transformation: An Aviation Safety Anomaly Detection Case-Study
by: Asanjan, Ata Akbari, et al.
Published: (2026)

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

Graph Spatiotemporal Process for Multivariate Time Series Anomaly Detection with Missing Values
by: Zheng, Yu, et al.
Published: (2024)

Exploring Transformer Placement in Variational Autoencoders for Tabular Data Generation
by: Silva, Aníbal, et al.
Published: (2026)

Attention and Autoencoder Hybrid Model for Unsupervised Online Anomaly Detection
by: Najafi, Seyed Amirhossein, et al.
Published: (2024)

Modeling Quantum Federated Autoencoder for Anomaly Detection in IoT Networks
by: Chaudhary, Devashish, et al.
Published: (2026)

ReSAE: Residualized Sparse Autoencoders for Multi-Layer Transformer Interventions
by: Poduval, Prathyush, et al.
Published: (2026)

A Hybrid Autoencoder-Transformer Model for Robust Day-Ahead Electricity Price Forecasting under Extreme Conditions
by: Tang, Boyan, et al.
Published: (2025)

MeanFlow Transformers with Representation Autoencoders
by: Hu, Zheyuan, et al.
Published: (2025)

ACTIVA: Amortized Causal Effect Estimation via Transformer-based Variational Autoencoder
by: Sauter, Andreas, et al.
Published: (2025)

Foundation Models and Transformers for Anomaly Detection: A Survey
by: Ammar, Mouïn Ben, et al.
Published: (2025)

A Framework for Streaming Event-Log Prediction in Business Processes
by: Bollig, Benedikt, et al.
Published: (2024)

A Review of AI and Machine Learning Contribution in Predictive Business Process Management (Process Enhancement and Process Improvement Approaches)
by: Abbasi, Mostafa, et al.
Published: (2024)

Applying Quantum Autoencoders for Time Series Anomaly Detection
by: Frehner, Robin, et al.
Published: (2024)

Multiobjective Hydropower Reservoir Operation Optimization with Transformer-Based Deep Reinforcement Learning
by: Wu, Rixin, et al.
Published: (2023)

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

Self-supervised Learning Method Using Transformer for Multi-dimensional Sensor Data Processing
by: Kai, Haruki, et al.
Published: (2025)

Advancements in Generative AI: A Comprehensive Review of GANs, GPT, Autoencoders, Diffusion Model, and Transformers
by: Bengesi, Staphord, et al.
Published: (2023)

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

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

Multi-Head Spectral-Adaptive Graph Anomaly Detection
by: Cao, Qingyue, et al.
Published: (2025)

RESTAD: REconstruction and Similarity based Transformer for time series Anomaly Detection
by: Ghorbani, Ramin, et al.
Published: (2024)

Global Spatio-Temporal Fusion-based Traffic Prediction Algorithm with Anomaly Aware
by: Liu, Chaoqun, et al.
Published: (2024)

Harnessing Contrastive Learning and Neural Transformation for Time Series Anomaly Detection
by: Chen, Katrina, et al.
Published: (2023)

Uncertainty-Aware Generative Oversampling Using an Entropy-Guided Conditional Variational Autoencoder
by: Zare, Amirhossein, et al.
Published: (2025)