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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/fabrice-rossi/outlier-anomaly-detection

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Meta-survey on outlier and anomaly detection

https://github.com/fdudsde/magic

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MAGIC: Detecting Advanced Persistent Threats via Masked Graph Representation Learning

https://github.com/fluctuationod/fluctuation-based-outlier-detection

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Fluctuation-based Outlier Detection

https://github.com/goldenNormal/EntropyStop-KDD2024

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EntropyStop: Unsupervised Deep Outlier Detection with Loss Entropy

https://github.com/goldennormal/automatedtrainingod

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Unleashing the Potential of Unsupervised Deep Outlier Detection through Automated Training Stopping

https://github.com/goldennormal/vgod-github

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Unsupervised Graph Outlier Detection: Problem Revisit, New Insight, and Superior Method

https://github.com/google-research/deep_representation_one_class

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Learning and Evaluating Representations for Deep One-class Classification

https://github.com/google-research/google-research

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Robust outlier detection by de-biasing VAE likelihoods

https://github.com/google-research/google-research/tree/master/pruning_identified_exemplars

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What Do Compressed Deep Neural Networks Forget?

https://github.com/guanzihan/benign-samples-matter

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Benign Samples Matter! Fine-tuning On Outlier Benign Samples Severely Breaks Safety

https://github.com/hamilton-health-sciences/ml4h-traq

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Do Ensembling and Meta-Learning Improve Outlier Detection in Randomized Controlled Trials?

https://github.com/haomingsj98/rstgam

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Robust Spatiotemporal Epidemic Modeling with Integrated Adaptive Outlier Detection

https://github.com/heejokong/divcon

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Diversify and Conquer: Open-set Disagreement for Robust Semi-supervised Learning with Outliers

https://github.com/hendrycks/ss-ood

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Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty

https://github.com/herrmo/fda-geo-out

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A geometric perspective on functional outlier detection

https://github.com/himanshudce/owam

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Enhancing Traffic Flow Prediction using Outlier-Weighted AutoEncoders: Handling Real-Time Changes

https://github.com/homarques/DAO

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Dimensionality-Aware Outlier Detection: Theoretical and Experimental Analysis

https://github.com/imagingdatacommons/cloudsegmentatorresults

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Rule-based outlier detection of AI-generated anatomy segmentations

https://github.com/inspire-group/SSD

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SSD: A Unified Framework for Self-Supervised Outlier Detection

https://github.com/issaz/signature-regime-detection

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Non-parametric online market regime detection and regime clustering for multidimensional and path-dependent data structures

https://github.com/jandiers/ood-detection

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Out-of-Distribution Detection Using Outlier Detection Methods

https://github.com/jcribeiro98/bisect

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Efficient Generation of Hidden Outliers for Improved Outlier Detection

https://github.com/jcribeiro98/v-gan

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Adversarial Subspace Generation for Outlier Detection in High-Dimensional Data

https://github.com/jhy549/ocgec

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OCGEC: One-class Graph Embedding Classification for DNN Backdoor Detection

https://github.com/jingkang50/oodsurvey

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Generalized Out-of-Distribution Detection: A Survey

https://github.com/jingkang50/openood

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Generalized Out-of-Distribution Detection: A Survey

https://github.com/jshwang0311/odim

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ODIM: Outlier Detection via Likelihood of Under-Fitted Generative Models

https://github.com/jupall/lcpr-data

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Sliced-Wasserstein-based Anomaly Detection and Open Dataset for Localized Critical Peak Rebates

https://github.com/jupall/swfilter

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Sliced-Wasserstein-based Anomaly Detection and Open Dataset for Localized Critical Peak Rebates

https://github.com/juyeon999/oedpm

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Unsupervised Outlier Detection using Random Subspace and Subsampling Ensembles of Dirichlet Process Mixtures

https://github.com/jylins/hood

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Out-of-Distribution Detection with Hilbert-Schmidt Independence Optimization

https://github.com/kalmannet/oikf-nuv

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Outlier-Insensitive Kalman Filtering: Theory and Applications

https://github.com/kayzliu/godm

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Data Augmentation for Supervised Graph Outlier Detection via Latent Diffusion Models

https://github.com/kayzliu/tgtod

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TGTOD: A Global Temporal Graph Transformer for Outlier Detection at Scale

https://github.com/khalooei/ALOCC-CVPR2018

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Adversarially Learned One-Class Classifier for Novelty Detection

https://github.com/kopetri/HPSCAN

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HPSCAN: Human Perception-Based Scattered Data Clustering

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