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

Showing 150 of 703 papers

TitleStatusHype
Robust Spatiotemporal Epidemic Modeling with Integrated Adaptive Outlier DetectionCode0
Universal Embeddings of Tabular Data0
Hybrid Meta-Learning Framework for Anomaly Forecasting in Nonlinear Dynamical Systems via Physics-Inspired Simulation and Deep Ensembles0
Diversify and Conquer: Open-set Disagreement for Robust Semi-supervised Learning with OutliersCode0
LayerIF: Estimating Layer Quality for Large Language Models using Influence Functions0
Learning novel representations of variable sources from multi-modal Gaia data via autoencoders0
Re-experiment Smart: a Novel Method to Enhance Data-driven Prediction of Mechanical Properties of Epoxy Polymers0
Importance Sampling for Nonlinear ModelsCode0
Robust Indoor Localization via Conformal Methods and Variational Bayesian Adaptive Filtering0
Benign Samples Matter! Fine-tuning On Outlier Benign Samples Severely Breaks SafetyCode0
Conformal Prediction with Cellwise Outliers: A Detect-then-Impute Approach0
Comparison of Visual Trackers for Biomechanical Analysis of Running0
Extending Decision Predicate Graphs for Comprehensive Explanation of Isolation Forest0
A probabilistic view on Riemannian machine learning models for SPD matrices0
Unsupervised outlier detection to improve bird audio dataset labels0
Adaptive PCA-Based Outlier Detection for Multi-Feature Time Series in Space Missions0
Adversarial Subspace Generation for Outlier Detection in High-Dimensional DataCode0
Robust Randomized Low-Rank Approximation with Row-Wise Outlier Detection0
Evaluation of (Un-)Supervised Machine Learning Methods for GNSS Interference Classification with Real-World Data Discrepancies0
TRIDIS: A Comprehensive Medieval and Early Modern Corpus for HTR and NER0
PS-EIP: Robust Photometric Stereo Based on Event Interval Profile0
Oaken: Fast and Efficient LLM Serving with Online-Offline Hybrid KV Cache Quantization0
Highly Efficient Direct Analytics on Semantic-aware Time Series Data Compression0
Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model0
OuroMamba: A Data-Free Quantization Framework for Vision Mamba Models0
Robust Multi-Source Domain Adaptation under Label Shift0
Out-of-Distribution Detection on Graphs: A SurveyCode1
Robust Conformal Outlier Detection under Contaminated Reference DataCode0
CleanSurvival: Automated data preprocessing for time-to-event models using reinforcement learningCode0
RODEO: Robust Outlier Detection via Exposing Adaptive Out-of-Distribution SamplesCode0
Explainable and Robust Millimeter Wave Beam Alignment for AI-Native 6G Networks0
Class Imbalance in Anomaly Detection: Learning from an Exactly Solvable Model0
Temporal Analysis of Adversarial Attacks in Federated Learning0
Data Enrichment Opportunities for Distribution Grid Cable Networks using Variational Autoencoders0
Outlyingness Scores with Cluster Catch Digraphs0
On the Adversarial Robustness of Benjamini Hochberg0
Fuzzy Granule Density-Based Outlier Detection with Multi-Scale Granular BallsCode1
Transfer Neyman-Pearson Algorithm for Outlier Detection0
An Efficient Outlier Detection Algorithm for Data Streaming0
FlexUOD: The Answer to Real-world Unsupervised Image Outlier Detection0
Blockchain-Empowered Cyber-Secure Federated Learning for Trustworthy Edge Computing0
Testing and Improving the Robustness of Amortized Bayesian Inference for Cognitive ModelsCode0
Brain Ageing Prediction using Isolation Forest Technique and Residual Neural Network (ResNet)0
Efficient Curation of Invertebrate Image Datasets Using Feature Embeddings and Automatic Size ComparisonCode0
PyOD 2: A Python Library for Outlier Detection with LLM-powered Model SelectionCode0
GradStop: Exploring Training Dynamics in Unsupervised Outlier Detection through GradientCode0
Detecting outliers by clustering algorithms0
Backdooring Outlier Detection Methods: A Novel Attack Approach0
Leveraging Ensemble-Based Semi-Supervised Learning for Illicit Account Detection in Ethereum DeFi Transactions0
TGTOD: A Global Temporal Graph Transformer for Outlier Detection at ScaleCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1VRAE+SVMAccuracy0.98Unverified
2F-t ALSTM-FCNAccuracy0.95Unverified
3GENDISAccuracy0.94Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy99.03Unverified
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1ASVDDAverage Accuracy37.62Unverified
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1ASVDDAverage Accuracy65.6Unverified
#ModelMetricClaimedVerifiedStatus
1PAEAUROC1Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy99.05Unverified
#ModelMetricClaimedVerifiedStatus
1MIXAUC0.86Unverified
#ModelMetricClaimedVerifiedStatus
1MIXAUC-ROC0.85Unverified
#ModelMetricClaimedVerifiedStatus
1MIXAUC-ROC0.93Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy86.33Unverified
#ModelMetricClaimedVerifiedStatus
1LSTMCapsAverage F10.74Unverified