SOTAVerified

Outlier Detection

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

Papers

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Showing 51–100 of 703 papers

TitleStatusHype
Using Images to Find Context-Independent Word Representations in Vector Space—0
Unsupervised Event Outlier Detection in Continuous Time—0
Lower Dimensional Spherical Representation of Medium Voltage Load Profiles for Visualization, Outlier Detection, and Generative Modelling—0
Uncertainty in Supply Chain Digital Twins: A Quantum-Classical Hybrid Approach—0
Unsupervised Parameter-free Outlier Detection using HDBSCAN* Outlier Profiles—0
Enhancing Diversity in Bayesian Deep Learning via Hyperspherical Energy Minimization of CKACode0
GWQ: Gradient-Aware Weight Quantization for Large Language Models—0
Sliced-Wasserstein-based Anomaly Detection and Open Dataset for Localized Critical Peak RebatesCode0
A Review of Graph-Powered Data Quality Applications for IoT Monitoring Sensor Networks—0
Coniferest: a complete active anomaly detection frameworkCode1
Lifted Coefficient of Determination: Fast model-free prediction intervals and likelihood-free model comparison—0
ECORS: An Ensembled Clustering Approach to Eradicate The Local And Global Outlier In Collaborative Filtering Recommender System—0
Conditional Testing based on Localized Conformal p-values—0
Decision-change Informed Rejection Improves Robustness in Pattern Recognition-based Myoelectric Control—0
Outlier Detection with Cluster Catch Digraphs—0
Zero-shot Outlier Detection via Prior-data Fitted Networks: Model Selection Bygone!—0
Synthetic Data Generation and Automated Multidimensional Data Labeling for AI/ML in General and Circular Coordinates—0
Interpreting Outliers in Time Series Data through Decoding Autoencoder—0
Robust Statistical Scaling of Outlier Scores: Improving the Quality of Outlier Probabilities for Outliers (Extended Version)—0
Outlier Detection Bias Busted: Understanding Sources of Algorithmic Bias through Data-centric Factors—0
Flexible categorization using formal concept analysis and Dempster-Shafer theory—0
Multimodal Foundational Models for Unsupervised 3D General Obstacle Detection—0
ALTBI: Constructing Improved Outlier Detection Models via Optimization of Inlier-Memorization Effect—0
Impact of Comprehensive Data Preprocessing on Predictive Modelling of COVID-19 MortalityCode0
EOL: Transductive Few-Shot Open-Set Recognition by Enhancing Outlier LogitsCode0
Regularized Contrastive Partial Multi-view Outlier Detection—0
Outlier Detection in Large Radiological Datasets using UMAPCode0
STAMP: Outlier-Aware Test-Time Adaptation with Stable Memory ReplayCode1
BoBa: Boosting Backdoor Detection through Data Distribution Inference in Federated Learning—0
Rethinking Unsupervised Outlier Detection via Multiple ThresholdingCode0
SPINEX: Similarity-based Predictions with Explainable Neighbors Exploration for Anomaly and Outlier Detection—0
Machine Learning for Complex Systems with Abnormal Pattern by Exception Maximization Outlier Detection Method—0
M5 -- A Diverse Benchmark to Assess the Performance of Large Multimodal Models Across Multilingual and Multicultural Vision-Language Tasks—0
A Radiometric Correction based Optical Modeling Approach to Removing Reflection Noise in TLS Point Clouds of Urban ScenesCode0
Optimization of Retrieval-Augmented Generation Context with Outlier Detection—0
HAITCH: A Framework for Distortion and Motion Correction in Fetal Multi-Shell Diffusion-Weighted MRI—0
Statistical Test for Feature Selection Pipelines by Selective InferenceCode0
Evaluating the Efficacy of Foundational Models: Advancing Benchmarking Practices to Enhance Fine-Tuning Decision-Making—0
Rule-based outlier detection of AI-generated anatomy segmentationsCode0
Outlier detection in maritime environments using AIS data and deep recurrent architectures—0
Meta-learning for Positive-unlabeled Classification—0
Can Dense Connectivity Benefit Outlier Detection? An Odyssey with NAS—0
Comparative Study of Neighbor-based Methods for Local Outlier Detection—0
EntropyStop: Unsupervised Deep Outlier Detection with Loss EntropyCode0
Rethinking Graph Backdoor Attacks: A Distribution-Preserving PerspectiveCode1
A Method of Moments Embedding Constraint and its Application to Semi-Supervised LearningCode0
Fin-Fed-OD: Federated Outlier Detection on Financial Tabular Data—0
Generative Subspace Adversarial Active Learning for Outlier Detection in Multiple Views of High-dimensional DataCode0
Aggressive or Imperceptible, or Both: Network Pruning Assisted Hybrid Byzantines in Federated LearningCode0
Differential Privacy for Anomaly Detection: Analyzing the Trade-off Between Privacy and Explainability—0
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All datasetsECG5000Balance scale_class 1Breast cancer Wisconsin_class 2Breast cancer Wisconsin_class 4Fashion-MNISTGlass identificationHeart-CHepatitisInternet AdIonosphere_class bSKAB

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1VRAE+SVMAccuracy0.98—Unverified
2F-t ALSTM-FCNAccuracy0.95—Unverified
3GENDISAccuracy0.94—Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy99.03—Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy37.62—Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy65.6—Unverified
#ModelMetricClaimedVerifiedStatus
1PAEAUROC1—Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy99.05—Unverified
#ModelMetricClaimedVerifiedStatus
1MIXAUC0.86—Unverified
#ModelMetricClaimedVerifiedStatus
1MIXAUC-ROC0.85—Unverified
#ModelMetricClaimedVerifiedStatus
1MIXAUC-ROC0.93—Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy86.33—Unverified
#ModelMetricClaimedVerifiedStatus
1LSTMCapsAverage F10.74—Unverified