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 451–500 of 703 papers

TitleStatusHype
Universal Embeddings of Tabular Data—0
Outlier detection at the parcel-level in wheat and rapeseed crops using multispectral and SAR time series—0
Unsupervised Deep One-Class Classification with Adaptive Threshold based on Training Dynamics—0
Unsupervised Event Outlier Detection in Continuous Time—0
Unsupervised outlier detection to improve bird audio dataset labels—0
Unsupervised Outlier Detection using Memory and Contrastive Learning—0
Unsupervised Parameter-free Outlier Detection using HDBSCAN* Outlier Profiles—0
Unsupervised routine discovery in egocentric photo-streams—0
Unsupervised Time Series Outlier Detection with Diversity-Driven Convolutional Ensembles -- Extended Version—0
User Equipment Assisted Localization for 6G Integrated Sensing and Communication—0
Using Eigencentrality to Estimate Joint, Conditional and Marginal Probabilities from Mixed-Variable Data: Method and Applications—0
Using Images to Find Context-Independent Word Representations in Vector Space—0
Validating and Exploring Large Geographic Corpora—0
Truncated Gaussian-Mixture Variational AutoEncoder—0
Versatile Anomaly Detection with Outlier Preserving Distribution Mapping Autoencoders—0
Visualizing and Exploring Dynamic High-Dimensional Datasets with LION-tSNE—0
Weighting vectors for machine learning: numerical harmonic analysis applied to boundary detection—0
WePaMaDM-Outlier Detection: Weighted Outlier Detection using Pattern Approaches for Mass Data Mining—0
What do we learn? Debunking the Myth of Unsupervised Outlier Detection—0
What goes around comes around: Cycle-Consistency-based Short-Term Motion Prediction for Anomaly Detection using Generative Adversarial Networks—0
When Complexity Is Good: Do We Need Recurrent Deep Learning For Time Series Outlier Detection?—0
Zero-shot Outlier Detection via Prior-data Fitted Networks: Model Selection Bygone!—0
Zipporah: a Fast and Scalable Data Cleaning System for Noisy Web-Crawled Parallel Corpora—0
Consensus Clustering: An Embedding Perspective, Extension and Beyond—0
3D Labeling Tool—0
3D Scanning: A Comprehensive Survey—0
A Bayesian Ensemble for Unsupervised Anomaly Detection—0
A boosted outlier detection method based on the spectrum of the Laplacian matrix of a graph—0
About Test-time training for outlier detection—0
Achieving differential privacy for k-nearest neighbors based outlier detection by data partitioning—0
A Comprehensive System for Secondary Structure Analysis of Protein Models—0
Active Learning of SVDD Hyperparameter Values—0
Active Relation Discovery: Towards General and Label-aware OpenRE—0
Active Relation Discovery: Towards General and Label-aware Open Relation Extraction—0
Adaptive Double-Exploration Tradeoff for Outlier Detection—0
Adaptive Outlier Detection for Power MOSFETs Based on Gaussian Process Regression—0
Adaptive PCA-Based Outlier Detection for Multi-Feature Time Series in Space Missions—0
Incremental Data-driven Optimization of Complex Systems in Nonstationary Environments—0
A Deep Learning Anomaly Detection Method in Textual Data—0
A deep mixture density network for outlier-corrected interpolation of crowd-sourced weather data—0
A feature construction framework based on outlier detection and discriminative pattern mining—0
A Framework for Clustering Uncertain Data—0
A Framework for Developing and Evaluating Word Embeddings of Drug-named Entity—0
A General Framework for Density Based Time Series Clustering Exploiting a Novel Admissible Pruning Strategy—0
A geometric framework for outlier detection in high-dimensional data—0
A Hybrid Deep Feature-Based Deformable Image Registration Method for Pathology Images—0
A Hybrid Intelligent Framework for Maximising SAG Mill Throughput: An Integration of Expert Knowledge, Machine Learning and Evolutionary Algorithms for Parameter Optimisation—0
A Joint Indoor WLAN Localization and Outlier Detection Scheme Using LASSO and Elastic-Net Optimization Techniques—0
A Large-scale Study on Unsupervised Outlier Model Selection: Do Internal Strategies Suffice?—0
A Local Density-Based Approach for Local Outlier Detection—0
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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