:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zeng, Zezhen, Liu, Bin
Format:	Preprint
Published:	2023
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2309.02084
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Enclosing Prototypical Variational Autoencoder for Explainable Out-of-Distribution Detection
by: Orglmeister, Conrad, et al.
Published: (2025)

Out-of-Distribution Radar Detection in Compound Clutter and Thermal Noise through Variational Autoencoders
by: Rouzoumka, Y A, et al.
Published: (2025)

Structural Entropy Guided Unsupervised Graph Out-Of-Distribution Detection
by: Hou, Yue, et al.
Published: (2025)

Resultant: Incremental Effectiveness on Likelihood for Unsupervised Out-of-Distribution Detection
by: Li, Yewen, et al.
Published: (2024)

Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmark
by: Wang, Yili, et al.
Published: (2024)

Iterative Deployment Exposure for Unsupervised Out-of-Distribution Detection
by: Doorenbos, Lars, et al.
Published: (2024)

A Variational Information Theoretic Approach to Out-of-Distribution Detection
by: Mondal, Sudeepta, et al.
Published: (2025)

Beyond Vanilla Variational Autoencoders: Detecting Posterior Collapse in Conditional and Hierarchical Variational Autoencoders
by: Dang, Hien, et al.
Published: (2023)

Early Fault Detection on CMAPSS with Unsupervised LSTM Autoencoders
by: Sánchez, P., et al.
Published: (2026)

Feature Bank Enhancement for Distance-based Out-of-Distribution Detection
by: Liu, Yuhang, et al.
Published: (2025)

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders
by: Xie, Tianyu, et al.
Published: (2025)

Learning Non-Linear Invariants for Unsupervised Out-of-Distribution Detection
by: Doorenbos, Lars, et al.
Published: (2024)

An Unsupervised Adversarial Autoencoder for Cyber Attack Detection in Power Distribution Grids
by: Zideh, Mehdi Jabbari, et al.
Published: (2024)

Aggregation of Dependent Expert Distributions in Multimodal Variational Autoencoders
by: Mancisidor, Rogelio A, et al.
Published: (2025)

Superposition as Lossy Compression: Measure with Sparse Autoencoders and Connect to Adversarial Vulnerability
by: Bereska, Leonard, et al.
Published: (2025)

An Introduction to Discrete Variational Autoencoders
by: Jeffares, Alan, et al.
Published: (2025)

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

Unsupervised Multiple Domain Translation through Controlled Disentanglement in Variational Autoencoder
by: Almudévar, Antonio, et al.
Published: (2024)

Exploring Variational Graph Autoencoders for Distribution Grid Data Generation
by: Abbas, Syed Zain, et al.
Published: (2025)

Discovering Influential Factors in Variational Autoencoders
by: Liu, Shiqi, et al.
Published: (2018)

Steam Turbine Anomaly Detection: An Unsupervised Learning Approach Using Enhanced Long Short-Term Memory Variational Autoencoder
by: Xu, Weiming, et al.
Published: (2024)

Unsupervised High Impedance Fault Detection Using Autoencoder and Principal Component Analysis
by: Liu, Yingxiang, et al.
Published: (2023)

Direction-Aware Offline-to-Online Learning in Linear Contextual Bandits
by: Han, Zean, et al.
Published: (2026)

CR-LSO: Convex Neural Architecture Optimization in the Latent Space of Graph Variational Autoencoder with Input Convex Neural Networks
by: Rao, Xuan, et al.
Published: (2022)

Zero-Variance Gradients for Variational Autoencoders
by: Shao, Zilei, et al.
Published: (2025)

Unveiling Multiple Descents in Unsupervised Autoencoders
by: Rahimi, Kobi, et al.
Published: (2024)

Cascade-KDE: Robust Time-Series Restoration under Out-of-Distribution Impulse Corruptions
by: Liu, Yuefeng, et al.
Published: (2026)

Out-of-Distribution Detection on Graphs: A Survey
by: Cai, Tingyi, et al.
Published: (2025)

Weakly Augmented Variational Autoencoder in Time Series Anomaly Detection
by: Wu, Zhangkai, et al.
Published: (2024)

LSTM VS. Feed-Forward Autoencoders for Unsupervised Fault Detection in Hydraulic Pumps
by: Sánchez, P., et al.
Published: (2026)

Quadratic Neuron-empowered Heterogeneous Autoencoder for Unsupervised Anomaly Detection
by: Liao, Jing-Xiao, et al.
Published: (2022)

Diffusion-based Layer-wise Semantic Reconstruction for Unsupervised Out-of-Distribution Detection
by: Yang, Ying, et al.
Published: (2024)

AR-Flow VAE: A Structured Autoregressive Flow Prior Variational Autoencoder for Unsupervised Blind Source Separation
by: Wei, Yuan-Hao, et al.
Published: (2026)

Quorum: Zero-Training Unsupervised Anomaly Detection using Quantum Autoencoders
by: Ludmir, Jason Zev, et al.
Published: (2025)

Ensembled Cold-Diffusion Restorations for Unsupervised Anomaly Detection
by: Marimont, Sergio Naval, et al.
Published: (2024)

Out-of-Distribution Detection with Overlap Index
by: Fu, Hao, et al.
Published: (2024)

Kernel PCA for Out-of-Distribution Detection
by: Fang, Kun, et al.
Published: (2024)

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

Hybrid Quantum-Classical Autoencoders for Unsupervised Network Intrusion Detection
by: Rasyidi, Mohammad Arif, et al.
Published: (2025)

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