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Anomaly Detection

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하위 태스크: 28
평가표: 76
보존된 평가 기록: 669

Anomaly Detection is a binary classification identifying unusual or unexpected patterns in a dataset, which deviate significantly from the majority of the data. The goal of anomaly detection is to identify such anomalies, which could represent errors, fraud, or other types of unusual events, and flag them for further investigation.

[Image source]: GAN-based Anomaly Detection in Imbalance Problems

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/ericlee0224/pad

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PAD: A Dataset and Benchmark for Pose-agnostic Anomaly Detection

https://github.com/ericssonresearch/eon

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QBSD: Quartile-Based Seasonality Decomposition for Cost-Effective RAN KPI Forecasting

https://github.com/erktkdg/MTFL

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MTFL: Multi-Timescale Feature Learning for Weakly-Supervised Anomaly Detection in Surveillance Videos

https://github.com/ermongroup/NDA

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Negative Data Augmentation

https://github.com/esa/gaia-astrometric-exoplanet-orbit-ml

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Machine learning-based identification of Gaia astrometric exoplanet orbits

https://github.com/euranova/F1-Score-is-Biased

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Anomaly Detection: How to Artificially Increase your F1-Score with a Biased Evaluation Protocol

https://github.com/evenrose/CMDIAD

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Incomplete Multimodal Industrial Anomaly Detection via Cross-Modal Distillation

https://github.com/evotestops/loglead

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LogLead -- Fast and Integrated Log Loader, Enhancer, and Anomaly Detector

https://github.com/exathlonbenchmark/divad

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Unsupervised Anomaly Detection in Multivariate Time Series across Heterogeneous Domains

https://github.com/exathlonbenchmark/exathlon

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Exathlon: A Benchmark for Explainable Anomaly Detection over Time Series

https://github.com/explorerlu1024/mimad-gan

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MIM-GAN-based Anomaly Detection for Multivariate Time Series Data

https://github.com/eyalgut/TLR_anomaly_detection

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Temporal anomaly detection: calibrating the surprise

https://github.com/eyecan-ai/eyecandies

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The Eyecandies Dataset for Unsupervised Multimodal Anomaly Detection and Localization

https://github.com/eyr3/fltracer

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FLTracer: Accurate Poisoning Attack Provenance in Federated Learning

https://github.com/fabiocarrara/cbigan-ad

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Combining GANs and AutoEncoders for Efficient Anomaly Detection

https://github.com/fabrice-rossi/outlier-anomaly-detection

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Meta-survey on outlier and anomaly detection

https://github.com/facebookresearch/TimeSformer

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Is Space-Time Attention All You Need for Video Understanding?

https://github.com/facebookresearch/kats

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MOSPAT: AutoML based Model Selection and Parameter Tuning for Time Series Anomaly Detection

https://github.com/fahadsohrab/essvdd

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Ellipsoidal Subspace Support Vector Data Description

https://github.com/fahadsohrab/gessvdd

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Graph-Embedded Subspace Support Vector Data Description

https://github.com/fahadsohrab/mssvdd

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Multimodal Subspace Support Vector Data Description

https://github.com/fahadsohrab/ssvdd

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Subspace Support Vector Data Description

https://github.com/fair4hep/pfin4uqad

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Evidential Deep Learning for Uncertainty Quantification and Out-of-Distribution Detection in Jet Identification using Deep Neural Networks

https://github.com/falihgoz/cgad

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Entropy Causal Graphs for Multivariate Time Series Anomaly Detection

https://github.com/fancangning/anomaly_detection_transfer

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Importance Weighted Adversarial Discriminative Transfer for Anomaly Detection

https://github.com/fangzhenzhao/anomalydetection-keras

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A Uniform Framework for Anomaly Detection in Deep Neural Networks

https://github.com/fanxingliu2020/fedtadbench

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FedTADBench: Federated Time-Series Anomaly Detection Benchmark

https://github.com/fanzhenliu/dagad

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DAGAD: Data Augmentation for Graph Anomaly Detection

https://github.com/faraz2023/COVIDomaly

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Anomaly Detection Approach to Identify Early Cases in a Pandemic using Chest X-rays

https://github.com/farzad-bz/DeCo-Diff

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Correcting Deviations from Normality: A Reformulated Diffusion Model for Multi-Class Unsupervised Anomaly Detection

https://github.com/farzad-bz/mad-ad

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MAD-AD: Masked Diffusion for Unsupervised Brain Anomaly Detection

https://github.com/fbrad/diffusionae

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Time Series Anomaly Detection using Diffusion-based Models

https://github.com/fdjingliu/dmad

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A Survey on Diffusion Models for Anomaly Detection

https://github.com/fdjingliu/nsvad

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Networking Systems for Video Anomaly Detection: A Tutorial and Survey

https://github.com/feedzai/research-aml-elliptic

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Machine learning methods to detect money laundering in the Bitcoin blockchain in the presence of label scarcity

https://github.com/felime/brain_sas_baseline

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Challenging Current Semi-Supervised Anomaly Segmentation Methods for Brain MRI

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