Dealing with Uncertainty in Contextual Anomaly Detection
Fuente:
arXiv
Saved in:
| Main Authors: | Bindini, Luca, Perini, Lorenzo, Nistri, Stefano, Davis, Jesse, Frasconi, Paolo |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
MARS: Sound Generation via Multi-Channel Autoregression on Spectrograms
by: Ristori, Eleonora, et al.
Published: (2025)
by: Ristori, Eleonora, et al.
Published: (2025)
Uncertainty-aware Evaluation of Auxiliary Anomalies with the Expected Anomaly Posterior
by: Perini, Lorenzo, et al.
Published: (2024)
by: Perini, Lorenzo, et al.
Published: (2024)
Deep Neural Network Benchmarks for Selective Classification
by: Pugnana, Andrea, et al.
Published: (2024)
by: Pugnana, Andrea, et al.
Published: (2024)
Machine Learning with a Reject Option: A survey
by: Hendrickx, Kilian, et al.
Published: (2021)
by: Hendrickx, Kilian, et al.
Published: (2021)
Out of Context: Reliability in Multimodal Anomaly Detection Requires Contextual Inference
by: Wilkinghoff, Kevin, et al.
Published: (2026)
by: Wilkinghoff, Kevin, et al.
Published: (2026)
Uncertainty-aware Human Mobility Modeling and Anomaly Detection
by: Wen, Haomin, et al.
Published: (2024)
by: Wen, Haomin, et al.
Published: (2024)
RangeAD: Fast On-Model Anomaly Detection
by: Hinkamp, Luca, et al.
Published: (2026)
by: Hinkamp, Luca, et al.
Published: (2026)
Explaining Deep Learning-based Anomaly Detection in Energy Consumption Data by Focusing on Contextually Relevant Data
by: Noorchenarboo, Mohammad, et al.
Published: (2025)
by: Noorchenarboo, Mohammad, et al.
Published: (2025)
Leveraging GPT-4o Efficiency for Detecting Rework Anomaly in Business Processes
by: Derakhshan, Mohammad, et al.
Published: (2025)
by: Derakhshan, Mohammad, et al.
Published: (2025)
Adaptive and Explainable AI Agents for Anomaly Detection in Critical IoT Infrastructure using LLM-Enhanced Contextual Reasoning
by: Sharma, Raghav, et al.
Published: (2025)
by: Sharma, Raghav, et al.
Published: (2025)
Multiclass Local Calibration with the Jensen-Shannon Distance
by: Barbera, Cesare, et al.
Published: (2025)
by: Barbera, Cesare, et al.
Published: (2025)
Divide et Calibra: Multiclass Local Calibration via Vector Quantization
by: Barbera, Cesare, et al.
Published: (2026)
by: Barbera, Cesare, et al.
Published: (2026)
uLEAD-TabPFN: Uncertainty-aware Dependency-based Anomaly Detection with TabPFN
by: Lu, Sha, et al.
Published: (2026)
by: Lu, Sha, et al.
Published: (2026)
Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model
by: Zanger, Moritz A., et al.
Published: (2025)
by: Zanger, Moritz A., et al.
Published: (2025)
Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector
by: Toor, Aafan Ahmad, et al.
Published: (2025)
by: Toor, Aafan Ahmad, et al.
Published: (2025)
Beyond Feature Fusion: Contextual Bayesian PEFT for Multimodal Uncertainty Estimation
by: Naderi, Habibeh, et al.
Published: (2026)
by: Naderi, Habibeh, et al.
Published: (2026)
Deal, or no deal (or who knows)? Forecasting Uncertainty in Conversations using Large Language Models
by: Sicilia, Anthony, et al.
Published: (2024)
by: Sicilia, Anthony, et al.
Published: (2024)
Possibility for Proactive Anomaly Detection
by: Jeon, Jinsung, et al.
Published: (2025)
by: Jeon, Jinsung, et al.
Published: (2025)
Autoencoders for Anomaly Detection are Unreliable
by: Bouman, Roel, et al.
Published: (2025)
by: Bouman, Roel, et al.
Published: (2025)
Unsupervised Surrogate Anomaly Detection
by: Klüttermann, Simon, et al.
Published: (2025)
by: Klüttermann, Simon, et al.
Published: (2025)
On Diffusion Modeling for Anomaly Detection
by: Livernoche, Victor, et al.
Published: (2023)
by: Livernoche, Victor, et al.
Published: (2023)
Enhanced Water Leak Detection with Convolutional Neural Networks and One-Class Support Vector Machine
by: Leonzio, Daniele Ugo, et al.
Published: (2025)
by: Leonzio, Daniele Ugo, et al.
Published: (2025)
Topological Uncertainty for Anomaly Detection in the Neural-network EoS Inference with Neutron Star Data
by: Fukushima, Kenji, et al.
Published: (2025)
by: Fukushima, Kenji, et al.
Published: (2025)
Uncertainty Estimation by Human Perception versus Neural Models
by: Mendes, Pedro, et al.
Published: (2025)
by: Mendes, Pedro, et al.
Published: (2025)
Graph Enhanced Trajectory Anomaly Detection
by: Mbuya, Jonathan Kabala, et al.
Published: (2025)
by: Mbuya, Jonathan Kabala, et al.
Published: (2025)
Graph Evidential Learning for Anomaly Detection
by: Wei, Chunyu, et al.
Published: (2025)
by: Wei, Chunyu, et al.
Published: (2025)
Anomaly Detection for Incident Response at Scale
by: Wang, Hanzhang, et al.
Published: (2024)
by: Wang, Hanzhang, et al.
Published: (2024)
Trajectory Anomaly Detection with Language Models
by: Mbuya, Jonathan, et al.
Published: (2024)
by: Mbuya, Jonathan, et al.
Published: (2024)
Masked Diffusion Modeling for Anomaly Detection
by: Zhang, Lixing, et al.
Published: (2026)
by: Zhang, Lixing, et al.
Published: (2026)
AnomalyGFM: Graph Foundation Model for Zero/Few-shot Anomaly Detection
by: Qiao, Hezhe, et al.
Published: (2025)
by: Qiao, Hezhe, et al.
Published: (2025)
M$^2$AD: Multi-Sensor Multi-System Anomaly Detection through Global Scoring and Calibrated Thresholding
by: Alnegheimish, Sarah, et al.
Published: (2025)
by: Alnegheimish, Sarah, et al.
Published: (2025)
Enhancing Anomaly Detection via Generating Diversified and Hard-to-distinguish Synthetic Anomalies
by: Kim, Hyuntae, et al.
Published: (2024)
by: Kim, Hyuntae, et al.
Published: (2024)
Hashing for Structure-based Anomaly Detection
by: Leveni, Filippo, et al.
Published: (2025)
by: Leveni, Filippo, et al.
Published: (2025)
Reasoning-based Anomaly Detection Framework: A Real-time, Scalable, and Automated Approach to Anomaly Detection Across Domains
by: Panwar, Anupam, et al.
Published: (2025)
by: Panwar, Anupam, et al.
Published: (2025)
Measuring multi-calibration
by: Guy, Ido, et al.
Published: (2025)
by: Guy, Ido, et al.
Published: (2025)
CLUE: Neural Networks Calibration via Learning Uncertainty-Error alignment
by: Mendes, Pedro, et al.
Published: (2025)
by: Mendes, Pedro, et al.
Published: (2025)
Foundation Models for Anomaly Detection: Vision and Challenges
by: Ren, Jing, et al.
Published: (2025)
by: Ren, Jing, et al.
Published: (2025)
A Survey on Diffusion Models for Anomaly Detection
by: Liu, Jing, et al.
Published: (2025)
by: Liu, Jing, et al.
Published: (2025)
Kinematic Detection of Anomalies in Human Trajectory Data
by: Kennedy, Lance, et al.
Published: (2024)
by: Kennedy, Lance, et al.
Published: (2024)
Deep Orthogonal Hypersphere Compression for Anomaly Detection
by: Zhang, Yunhe, et al.
Published: (2023)
by: Zhang, Yunhe, et al.
Published: (2023)
Similar Items
-
MARS: Sound Generation via Multi-Channel Autoregression on Spectrograms
by: Ristori, Eleonora, et al.
Published: (2025) -
Uncertainty-aware Evaluation of Auxiliary Anomalies with the Expected Anomaly Posterior
by: Perini, Lorenzo, et al.
Published: (2024) -
Deep Neural Network Benchmarks for Selective Classification
by: Pugnana, Andrea, et al.
Published: (2024) -
Machine Learning with a Reject Option: A survey
by: Hendrickx, Kilian, et al.
Published: (2021) -
Out of Context: Reliability in Multimodal Anomaly Detection Requires Contextual Inference
by: Wilkinghoff, Kevin, et al.
Published: (2026)