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Outlier Detection

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하위 태스크: 4
평가표: 11
보존된 평가 기록: 13

Outlier Detection is a task of identifying a subset of a given data set which are considered anomalous in that they are unusual from other instances. It is one of the core data mining tasks and is central to many applications. In the security field, it can be used to identify potentially threatening users, in the manufacturing field it can be used to identify parts that are likely to fail.

Source: Coverage-based Outlier Explanation

코드

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

https://github.com/rohban-lab/rodeo

공식 코드

RODEO: Robust Outlier Detection via Exposing Adaptive Out-of-Distribution Samples

https://github.com/ronniemi/explainAnomaliesUsingSHAP

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Explaining Anomalies Detected by Autoencoders Using SHAP

https://github.com/sana33/SDCOR

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SDCOR: Scalable Density-based Clustering for Local Outlier Detection in Massive-Scale Datasets

https://github.com/sara-es/outlier-detection-recap-data

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Outlier detection of vital sign trajectories from COVID-19 patients

https://github.com/selgroup/sled

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Unsupervised Skin Lesion Segmentation via Structural Entropy Minimization on Multi-Scale Superpixel Graphs

https://github.com/sfme/RVAE_MixedTypes

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Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data

https://github.com/sfme/clsvae-error-repair

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Repairing Systematic Outliers by Learning Clean Subspaces in VAEs

https://github.com/sgraine/bag-of-seagrass

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Image Labels Are All You Need for Coarse Seagrass Segmentation

https://github.com/shanay-mehta/anomaly-benchmarking

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Can Tree Based Approaches Surpass Deep Learning in Anomaly Detection? A Benchmarking Study

https://github.com/sherrylixuecheng/odbo

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ODBO: Bayesian Optimization with Search Space Prescreening for Directed Protein Evolution

https://github.com/shirara1016/statistical_test_for_feature_selection_pipelines

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Statistical Test for Feature Selection Pipelines by Selective Inference

https://github.com/shuxiaoc/outference

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Valid Inference Corrected for Outlier Removal

https://github.com/siqil/CPPOD

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Event Outlier Detection in Continuous Time

https://github.com/snad-space/coniferest

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Coniferest: a complete active anomaly detection framework

https://github.com/snetbl/potatoes

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Anomaly Detection With Partitioning Overfitting Autoencoder Ensembles

https://github.com/snowood1/BERT-ENN

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Uncertainty-Aware Reliable Text Classification

https://github.com/snowood1/wenn

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Multidimensional Uncertainty-Aware Evidential Neural Networks

https://github.com/songyyyy/kdd22-oodgat

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Learning on Graphs with Out-of-Distribution Nodes

https://github.com/stephanieger/sequence-anomaly-detection

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Autoencoders and Generative Adversarial Networks for Imbalanced Sequence Classification

https://github.com/sumeetsk/maxgap_bandit

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MaxGap Bandit: Adaptive Algorithms for Approximate Ranking

https://github.com/supriya-pandhre/STWalk

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STWalk: Learning Trajectory Representations in Temporal Graphs

https://github.com/swyoon/normalized-autoencoders

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Autoencoding Under Normalization Constraints

https://github.com/taghikhah/quantod

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Quantile-based Maximum Likelihood Training for Outlier Detection

https://github.com/taolicheng/VAE-Jet

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Variational Autoencoders for Anomalous Jet Tagging

https://github.com/tariqul-islam/Outlier_Detection_UMAP

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Outlier Detection in Large Radiological Datasets using UMAP

https://github.com/thu-ml/ood-dgm

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Further Analysis of Outlier Detection with Deep Generative Models

https://github.com/titu1994/LSTM-FCN

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LSTM Fully Convolutional Networks for Time Series Classification

https://github.com/torchdrift/partial-wasserstein

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Partial Wasserstein and Maximum Mean Discrepancy distances for bridging the gap between outlier detection and drift detection

https://github.com/trent-b/unisel

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Unsupervised Instance Selection with Low-Label, Supervised Learning for Outlier Detection

https://github.com/trust-tuda/crowdguard

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CrowdGuard: Federated Backdoor Detection in Federated Learning

https://github.com/twistedcubic/que-outlier-detection

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Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier Detection

https://github.com/twugithub/2024-aistats-ortlrr

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Robust Data Clustering with Outliers via Transformed Tensor Low-Rank Representation

https://github.com/uri-abd/clam

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Clustered Hierarchical Anomaly and Outlier Detection Algorithms

https://github.com/vasco95/DMGD

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Integrating Network Embedding and Community Outlier Detection via Multiclass Graph Description

https://github.com/vladan-stojnic/active-outliers

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Training Ensembles with Inliers and Outliers for Semi-supervised Active Learning

https://github.com/vmboehm/pae-ablation

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Probabilistic Autoencoder

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