Anomaly Detector

Anomaly detection aims to identify data points deviating from expected patterns, crucial for various applications like predictive maintenance and cybersecurity. Current research emphasizes improving the accuracy and explainability of anomaly detection, focusing on models like autoencoders, variational autoencoders, and recurrent neural networks (RNNs), often incorporating techniques such as dynamic time warping and counterfactual explanations. These advancements are driving progress in diverse fields, enabling more robust systems for fault diagnosis, fraud detection, and improved safety in critical infrastructure.

Papers

October 24, 2024

A Unimodal Speaker-Level Membership Inference Detector for Contrastive Pretraining
Ruoxi Cheng, Yizhong Ding, Shuirong Cao, Shitong Shao, Zhiqiang Wang
Contrastive Example Membership Inference Anomaly Detector Contrastive Language Audio Pretraining

August 21, 2024

Explainable Anomaly Detection: Counterfactual driven What-If Analysis
Logan Cummins, Alexander Sommers, Sudip Mittal, Shahram Rahimi, Maria Seale, Joseph Jaboure, Thomas Arnold
Anomaly Detection Explainable AI Counterfactual Explanation High Quality Counterfactuals Anomaly Detector Explainable Anomaly Detection

August 9, 2024

Performance Metric for Multiple Anomaly Score Distributions with Discrete Severity Levels
Wonjun Yi, Yong-Hwa Park, Wonho Jung
Anomaly Score Performance Metric ROC Curve Anomaly Detector Severity Classification Anomaly Data

May 30, 2024

Joint Selective State Space Model and Detrending for Robust Time Series Anomaly Detection
Junqi Chen, Xu Tan, Sylwan Rahardja, Jiawei Yang, Susanto Rahardja
Long Range Dependency Selective State Space Anomaly Detector Selective State Space Model Sequence Generation Model

May 29, 2024

Deep Positive-Unlabeled Anomaly Detection for Contaminated Unlabeled Data
Hiroshi Takahashi, Tomoharu Iwata, Atsutoshi Kumagai, Yuuki Yamanaka
Training Data Anomaly Score Positive Unlabeled Learning Semi Supervised Anomaly Detection Anomaly Detector Anomaly Data

May 22, 2024

Uncertainty-aware Evaluation of Auxiliary Anomalies with the Expected Anomaly Posterior
Lorenzo Perini, Maja Rudolph, Sabrina Schmedding, Chen Qiu
Anomaly Detection Anomaly Detector Synthetic Anomaly

May 4, 2024

GAD: A Real-time Gait Anomaly Detection System with Online Adaptive Learning
Ming-Chang Lee, Jia-Chun Lin, Sokratis Katsikas
Adaptive Learning Human Gait Anomaly Detector Gait Detection

March 4, 2024

Unsupervised Distance Metric Learning for Anomaly Detection Over Multivariate Time Series
Hanyang Yuan, Qinglin Cai, Keting Yin
Anomaly Detection Multivariate Time Series Dynamic Time Warping Time Series Anomaly Detection Anomaly Detector Unsupervised Metric

February 22, 2024

February 20, 2024

FGAD: Self-boosted Knowledge Distillation for An Effective Federated Graph Anomaly Detection Framework
Jinyu Cai, Yunhe Zhang, Zhoumin Lu, Wenzhong Guo, See-kiong Ng
Anomaly Detection Knowledge Distillation Graph Anomaly Detection Anomaly Detector Anomalous Graph

February 14, 2024

Detection Latencies of Anomaly Detectors: An Overlooked Perspective ?
Tommaso Puccetti, Andrea Ceccarelli
Low Latency Error Detection Anomaly Detector Information Theoretic Detectability Based Intrusion Detection Overlooked Aspect

December 19, 2023

When Model Meets New Normals: Test-time Adaptation for Unsupervised Time-series Anomaly Detection
Dongmin Kim, Sunghyun Park, Jaegul Choo
Full Model Test Time Adaptation Time Series Anomaly Detection Anomaly Detector Unsupervised Time Series Anomaly Detection

November 30, 2023

Detecting Anomalous Network Communication Patterns Using Graph Convolutional Networks
Yizhak Vaisman, Gilad Katz, Yuval Elovici, Asaf Shabtai
Deep Convolutional Neural Network Variational Autoencoder Variational Graph Anomaly Detector

October 11, 2023

Learning a Cross-modality Anomaly Detector for Remote Sensing Imagery
Jingtao Li, Xinyu Wang, Hengwei Zhao, Liangpei Zhang, Yanfei Zhong
Anomaly Detection Different Modality Theatre Scene Description Anomaly Detector Least Absolute Deviation Detection Paradigm

October 10, 2023

May 22, 2023

AD-MERCS: Modeling Normality and Abnormality in Unsupervised Anomaly Detection
Jonas Soenen, Elia Van Wolputte, Vincent Vercruyssen, Wannes Meert, Hendrik Blockeel
Anomaly Detection Unsupervised Anomaly Detection UNsupervised Approach Anomaly Detection Performance Anomaly Detector Evident Abnormality

May 13, 2023

Description and Discussion on DCASE 2023 Challenge Task 2: First-Shot Unsupervised Anomalous Sound Detection for Machine Condition Monitoring
Kota Dohi, Keisuke Imoto, Noboru Harada, Daisuke Niizumi, Yuma Koizumi, Tomoya Nishida, Harsh Purohit, Ryo Tanabe, Takashi Endo, Yohei Kawaguchi
Data Detection Challenge Task Description Library Anomalous Sound Detection Acoustic Scene Robust Detection Anomaly Detector Machine Condition Monitoring

February 15, 2023

Zero-Shot Anomaly Detection via Batch Normalization
Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Maja Rudolph, Stephan Mandt
Anomaly Detection Batch Normalization Deep Anomaly Detection Zero Shot Anomaly Anomaly Detector

Anomaly Detector

Papers

A Unimodal Speaker-Level Membership Inference Detector for Contrastive Pretraining

Explainable Anomaly Detection: Counterfactual driven What-If Analysis

Performance Metric for Multiple Anomaly Score Distributions with Discrete Severity Levels

Joint Selective State Space Model and Detrending for Robust Time Series Anomaly Detection

Deep Positive-Unlabeled Anomaly Detection for Contaminated Unlabeled Data

Uncertainty-aware Evaluation of Auxiliary Anomalies with the Expected Anomaly Posterior

GAD: A Real-time Gait Anomaly Detection System with Online Adaptive Learning

Unsupervised Distance Metric Learning for Anomaly Detection Over Multivariate Time Series

Novelty Detection on Radio Astronomy Data using Signatures

Reimagining Anomalies: What If Anomalies Were Normal?

FGAD: Self-boosted Knowledge Distillation for An Effective Federated Graph Anomaly Detection Framework

Detection Latencies of Anomaly Detectors: An Overlooked Perspective ?

When Model Meets New Normals: Test-time Adaptation for Unsupervised Time-series Anomaly Detection

Detecting Anomalous Network Communication Patterns Using Graph Convolutional Networks

Learning a Cross-modality Anomaly Detector for Remote Sensing Imagery

A Supervised Embedding and Clustering Anomaly Detection method for classification of Mobile Network Faults

Assessing the Impact of a Supervised Classification Filter on Flow-based Hybrid Network Anomaly Detection

AD-MERCS: Modeling Normality and Abnormality in Unsupervised Anomaly Detection

Description and Discussion on DCASE 2023 Challenge Task 2: First-Shot Unsupervised Anomalous Sound Detection for Machine Condition Monitoring

Zero-Shot Anomaly Detection via Batch Normalization