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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/anindyasdas/adl4vad

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Adaptive Deviation Learning for Visual Anomaly Detection with Data Contamination

https://github.com/anncollin/AnomalyDetection-Keras

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Improved anomaly detection by training an autoencoder with skip connections on images corrupted with Stain-shaped noise

https://github.com/anniran1/hacd1-wsdm

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HACD: Harnessing Attribute Semantics and Mesoscopic Structure for Community Detection

https://github.com/anomalyllm/anomalyllm

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AnomalyLLM: Few-shot Anomaly Edge Detection for Dynamic Graphs using Large Language Models

https://github.com/anonymous-1-2-3-4/newzealandenergyprices

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Real-Time Energy Pricing in New Zealand: An Evolving Stream Analysis

https://github.com/anonymous-author-2021/omasgan

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OMASGAN: Out-of-Distribution Minimum Anomaly Score GAN for Sample Generation on the Boundary

https://github.com/anonymous-authors-repo/watermark_dataset

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Did You Train on My Dataset? Towards Public Dataset Protection with Clean-Label Backdoor Watermarking

https://github.com/antanaskascenas/denoisingae

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The role of noise in denoising models for anomaly detection in medical images

https://github.com/antoine-spahr/SELF-TAUGHT-SEMI-SUPERVISED-ANOMALY-DETECTION

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Self-Taught Semi-Supervised Anomaly Detection on Upper Limb X-rays

https://github.com/anupamaray/ensembleqml_application

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Classical ensemble of Quantum-classical ML algorithms for Phishing detection in Ethereum transaction networks

https://github.com/anurag14/inflow-prediction-bhakra

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Optimal Reservoir Operations using Long Short-Term Memory Network

https://github.com/aodongli/Active-SOEL

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Deep Anomaly Detection under Labeling Budget Constraints

https://github.com/aodongli/zero-shot-ad-via-batch-norm

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Zero-Shot Anomaly Detection via Batch Normalization

https://github.com/aoudsung/tri-crlad

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Semi-supervised Anomaly Detection via Adaptive Reinforcement Learning-Enabled Method with Causal Inference for Sensor Signals

https://github.com/apple/ml-destseg

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DeSTSeg: Segmentation Guided Denoising Student-Teacher for Anomaly Detection

https://github.com/architrathore/TopoAct

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TopoAct: Visually Exploring the Shape of Activations in Deep Learning

https://github.com/ari-dasci/autoencoder-showcase

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A Showcase of the Use of Autoencoders in Feature Learning Applications

https://github.com/ari-dasci/s-tsfe-dl

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TSFEDL: A Python Library for Time Series Spatio-Temporal Feature Extraction and Prediction using Deep Learning (with Appendices on Detailed Network Architectures and Experimental Cases of Study)

https://github.com/arielzc/de-net

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Dynamic Erasing Network Based on Multi-Scale Temporal Features for Weakly Supervised Video Anomaly Detection

https://github.com/arimousa/DDAD

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Anomaly Detection with Conditioned Denoising Diffusion Models

https://github.com/arnaudbougaham/tapauc

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Towards a Trustworthy Anomaly Detection for Critical Applications through Approximated Partial AUC Loss

https://github.com/arseniigav/dinamo

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DINAMO: Dynamic and INterpretable Anomaly MOnitoring for Large-Scale Particle Physics Experiments

https://github.com/aryan-jadon/regression-loss-functions-in-time-series-forecasting-tensorflow

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A Comprehensive Survey of Regression Based Loss Functions for Time Series Forecasting

https://github.com/asdvfghg/heterogeneous_autoencoder_by_quadratic_neurons

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Quadratic Neuron-empowered Heterogeneous Autoencoder for Unsupervised Anomaly Detection

https://github.com/aseuteurideu/LearningNotToReconstructAnomalies

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Learning Not to Reconstruct Anomalies

https://github.com/aseuteurideu/STEAL

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Synthetic Temporal Anomaly Guided End-to-End Video Anomaly Detection

https://github.com/astha-chem/mvts-ano-eval

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An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series

https://github.com/awatson246/crypto-anomaly-detection-policy

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Explain First, Trust Later: LLM-Augmented Explanations for Graph-Based Crypto Anomaly Detection

https://github.com/aws/random-cut-forest-by-aws

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Streaming Anomaly Detection

https://github.com/awslabs/gluon-ts/tree/master/src/gluonts/nursery/spliced_binned_pareto

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Spliced Binned-Pareto Distribution for Robust Modeling of Heavy-tailed Time Series

https://github.com/ayantikadas/unsupervised_anomaly_detection

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A Study of Representational Properties of Unsupervised Anomaly Detection in Brain MRI

https://github.com/aypan17/reward-misspecification

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The Effects of Reward Misspecification: Mapping and Mitigating Misaligned Models

https://github.com/b-deforce/tsa-on-autopilot

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TSA on AutoPilot: Self-tuning Self-supervised Time Series Anomaly Detection

https://github.com/bardhprenkaj/dynamo

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Unsupervised Detection of Behavioural Drifts with Dynamic Clustering and Trajectory Analysis

https://github.com/batmanlab/agxnet

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Anatomy-Guided Weakly-Supervised Abnormality Localization in Chest X-rays

https://github.com/bebillionaireusd/hades

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Heterogeneous Anomaly Detection for Software Systems via Semi-supervised Cross-modal Attention

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.