Cover Image

Performance Metric for Multiple Anomaly Score Distributions with Discrete Severity Levels

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yi, Wonjun, Park, Yong-Hwa, Jung, Wonho
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Cross-talk based multi-task learning for fault classification of machine system influenced by multiple variables
by: Yi, Wonjun, et al.
Published: (2026)

Multi-output Classification using a Cross-talk Architecture for Compound Fault Diagnosis of Motors in Partially Labeled Condition
by: Yi, Wonjun, et al.
Published: (2025)

Multi-output Classification for Compound Fault Diagnosis in Motor under Partially Labeled Target Domain
by: Yi, Wonjun, et al.
Published: (2025)

Multi-output Classification Framework and Frequency Layer Normalization for Compound Fault Diagnosis in Motor
by: Yi, Wonjun, et al.
Published: (2025)

Mitigating Long-Tailed Anomaly Score Distributions with Importance-Weighted Loss
by: Lee, Jungi, et al.
Published: (2026)

Random Is Hard to Beat: Active Selection in online DPO with Modern LLMs
by: Oh, Giyeong, et al.
Published: (2026)

Swift Hydra: Self-Reinforcing Generative Framework for Anomaly Detection with Multiple Mamba Models
by: Do, Nguyen, et al.
Published: (2025)

Guided Discrete Diffusion for Constraint Satisfaction Problems
by: Jung, Justin
Published: (2025)

Severing Spurious Correlations with Data Pruning
by: Mulchandani, Varun, et al.
Published: (2025)

Possibility for Proactive Anomaly Detection
by: Jeon, Jinsung, et al.
Published: (2025)

Kurtosis-Guided Denoising Score Matching for Tabular Anomaly Detection
by: Livernoche, Victor, et al.
Published: (2026)

When Will It Fail?: Anomaly to Prompt for Forecasting Future Anomalies in Time Series
by: Park, Min-Yeong, et al.
Published: (2025)

Spectral Clustering for Discrete Distributions
by: Wang, Zixiao, et al.
Published: (2024)

FANFOLD: Graph Normalizing Flows-driven Asymmetric Network for Unsupervised Graph-Level Anomaly Detection
by: Cao, Rui, et al.
Published: (2024)

AIS-LLM: A Unified Framework for Maritime Trajectory Prediction, Anomaly Detection, and Collision Risk Assessment with Explainable Forecasting
by: Park, Hyobin, et al.
Published: (2025)

From Parameter Dynamics to Risk Scoring : Quantifying Sample-Level Safety Degradation in LLM Fine-tuning
by: Wang, Xiao, et al.
Published: (2026)

Qsco: A Quantum Scoring Module for Open-set Supervised Anomaly Detection
by: Peng, Yifeng, et al.
Published: (2024)

Unsupervised Distance Metric Learning for Anomaly Detection Over Multivariate Time Series
by: Yuan, Hanyang, et al.
Published: (2024)

A Problem-Oriented Taxonomy of Evaluation Metrics for Time Series Anomaly Detection
by: Yang, Kaixiang, et al.
Published: (2025)

Revisiting Service Level Objectives and System Level Metrics in Large Language Model Serving
by: Wang, Zhibin, et al.
Published: (2024)

Improving Interpretability of Scores in Anomaly Detection Based on Gaussian-Bernoulli Restricted Boltzmann Machine
by: Sekimoto, Kaiji, et al.
Published: (2024)

Dynamic Mixture of Experts Against Severe Distribution Shifts
by: Kim, Donghu
Published: (2025)

GNN-ASE: Graph-Based Anomaly Detection and Severity Estimation in Three-Phase Induction Machines
by: Bentrad, Moutaz Bellah, et al.
Published: (2025)

Sufficient Invariant Learning for Distribution Shift
by: Kim, Taero, et al.
Published: (2022)

Enhancing Fairness in Autoencoders for Node-Level Graph Anomaly Detection
by: Wang, Shouju, et al.
Published: (2025)

Parameter-Efficient Token Embedding Editing for Clinical Class-Level Unlearning
by: Hou, Iyad Ait, et al.
Published: (2026)

Multiple-Input Variational Auto-Encoder for Anomaly Detection in Heterogeneous Data
by: Dinh, Phai Vu, et al.
Published: (2025)

Alleviating Structural Distribution Shift in Graph Anomaly Detection
by: Gao, Yuan, et al.
Published: (2024)

Effective Test-Time Scaling of Discrete Diffusion through Iterative Refinement
by: Lee, Sanghyun, et al.
Published: (2025)

Interpretable Graph-Level Anomaly Detection via Contrast with Normal Prototypes
by: Zhao, Qiuran, et al.
Published: (2026)

Meta-Learning Based Few-Shot Graph-Level Anomaly Detection
by: Li, Liting, et al.
Published: (2025)

DeepSTA: A Spatial-Temporal Attention Network for Logistics Delivery Timely Rate Prediction in Anomaly Conditions
by: Yi, Jinhui, et al.
Published: (2025)

Visualizing Uncertainty in Translation Tasks: An Evaluation of LLM Performance and Confidence Metrics
by: Park, Jin Hyun, et al.
Published: (2025)

Free Energy Manifold: Score-Based Inference for Hybrid Bayesian Networks
by: Park, Cheol Young, et al.
Published: (2026)

PaAno: Patch-Based Representation Learning for Time-Series Anomaly Detection
by: Park, Jinju, et al.
Published: (2026)

Martingale Score: An Unsupervised Metric for Bayesian Rationality in LLM Reasoning
by: He, Zhonghao, et al.
Published: (2025)

Metric Learning in an RKHS
by: Tatli, Gokcan, et al.
Published: (2025)

CIMAGE: Exploiting the Conditional Independence in Masked Graph Auto-encoders
by: Park, Jongwon, et al.
Published: (2025)

Imbalanced Graph-Level Anomaly Detection via Counterfactual Augmentation and Feature Learning
by: Wang, Zitong, et al.
Published: (2024)

Modeling Spatio-temporal Dynamical Systems with Neural Discrete Learning and Levels-of-Experts
by: Wang, Kun, et al.
Published: (2024)