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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://git.rwth-aachen.de/netsci/trajectory-outlier-detection-flow-embeddings

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Outlier Detection for Trajectories via Flow-embeddings

https://github.com/11hifish/d.mca

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D.MCA: Outlier Detection with Explicit Micro-Cluster Assignments

https://github.com/AhmedFrikha/ARCADe-A-Rapid-Continual-Anomaly-Detector

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ARCADe: A Rapid Continual Anomaly Detector

https://github.com/AhmedFrikha/Few-Shot-One-Class-Classification-via-Meta-Learning

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Few-Shot One-Class Classification via Meta-Learning

https://github.com/Basvanstein/Gloss

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Local Subspace-Based Outlier Detection using Global Neighbourhoods

https://github.com/CRYPTO-KU/FL-Byzantine-Library

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Aggressive or Imperceptible, or Both: Network Pruning Assisted Hybrid Byzantines in Federated Learning

https://github.com/ComputationalRadiationPhysics/InFlow

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InFlow: Robust outlier detection utilizing Normalizing Flows

https://github.com/Deep-Machine-Vision/he-cka-ensembles

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Enhancing Diversity in Bayesian Deep Learning via Hyperspherical Energy Minimization of CKA

https://github.com/Formsma/GAMA-outliers

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In search of the weirdest galaxies in the Universe

https://github.com/Gstaerman/FIF

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Outlier detection in multivariate functional data through a contaminated mixture model

https://github.com/HamedSarvari/Graph-Based-Selective-Outlier-Ensembles

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Graph-based Selective Outlier Ensembles

https://github.com/Hengwei-Zhao96/HOneCls

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One-Class Risk Estimation for One-Class Hyperspectral Image Classification

https://github.com/IBCNServices/GENDIS

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GENDIS: GENetic DIscovery of Shapelets

https://github.com/IljaManakov/WalkingTheTightrope

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Walking the Tightrope: An Investigation of the Convolutional Autoencoder Bottleneck

https://github.com/JWTHI/ViTAL-SCENE

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Novelty Detection and Analysis of Traffic Scenario Infrastructures in the Latent Space of a Vision Transformer-Based Triplet Autoencoder

https://github.com/Learner0x5a/kTrans-release

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kTrans: Knowledge-Aware Transformer for Binary Code Embedding

https://github.com/LingxiaoShawn/GLOD-Issues

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On Using Classification Datasets to Evaluate Graph-Level Outlier Detection: Peculiar Observations and New Insights

https://github.com/MJ10/DEUP

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DEUP: Direct Epistemic Uncertainty Prediction

https://github.com/MLforHealth/MIMIC_Extract

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MIMIC-Extract: A Data Extraction, Preprocessing, and Representation Pipeline for MIMIC-III

https://github.com/MasaKat0/D3RE

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Non-Negative Bregman Divergence Minimization for Deep Direct Density Ratio Estimation

https://github.com/NazirNayal8/RbA

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RbA: Segmenting Unknown Regions Rejected by All

https://github.com/OllieBoyne/FOUND

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FOUND: Foot Optimization with Uncertain Normals for Surface Deformation Using Synthetic Data

https://github.com/RomeroBarata/skeleton_based_anomaly_detection

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Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos

https://github.com/SJYuCNEL/Matrix-based-Dependence

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Measuring Dependence with Matrix-based Entropy Functional

https://github.com/Shubhranshu-Shekhar/fairOD

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FairOD: Fairness-aware Outlier Detection

https://github.com/SunWenJu123/DCPOC

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Exemplar-free Class Incremental Learning via Discriminative and Comparable One-class Classifiers

https://github.com/VMBoehm/PAE

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Probabilistic Autoencoder

https://github.com/VisionLearningGroup/OP_Match

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OpenMatch: Open-set Consistency Regularization for Semi-supervised Learning with Outliers

https://github.com/Yann-zh/gradAE

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GradStop: Exploring Training Dynamics in Unsupervised Outlier Detection through Gradient

https://github.com/aangelopoulos/ltt

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Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control

https://github.com/agoodge/lunar

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LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks

https://github.com/aldipiroli/semantic_spray_dataset

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Energy-based Detection of Adverse Weather Effects in LiDAR Data

https://github.com/alextimans/traffic4cast-uncertainty

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Uncertainty Quantification for Image-based Traffic Prediction across Cities

https://github.com/alphaprime/ROE

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Robust Ordinal Embedding from Contaminated Relative Comparisons

https://github.com/amazon-research/patchcore-inspection

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Towards Total Recall in Industrial Anomaly Detection

https://github.com/ananya-joshi/ijcai23_supplemental

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Computationally Assisted Quality Control for Public Health Data Streams

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