66 citations · 114 across the 10 of their papers we have counts for
6 papers · 1 filter
VACE: Learning Geometrically Structured Representations for Time Series Anomaly Detection
Alberto D. Cencillo, Leonardo Concepción, Isaac Triguero +1
Anomaly detection in multivariate time series is a critical task across a wide range of real-world applications, where abnormal behaviour is rare, labels are unavailable, and the c…
Lightweight CNN-Based Anomaly Detection for High Voltage Converter Modulators in the Spallation Neutron Source
Alberto D. Cencillo, Leonardo Concepción, Julián Luengo +1
Time series anomaly detection is central to monitoring industrial and scientific equipment, where anomalous sensor readings can precede failures. As such equipment usually carries…
STOOD-X methodology: using statistical nonparametric test for OOD Detection Large-Scale datasets enhanced with explainability
Iván Sevillano-García, Julián Luengo, Francisco Herrera
Out-of-Distribution (OOD) detection is a critical task in machine learning, particularly in safety-sensitive applications where model failures can have serious consequences. Howeve…
Local Attention Mechanism: Boosting the Transformer Architecture for Long-Sequence Time Series Forecasting
Ignacio Aguilera-Martos, Andrés Herrera-Poyatos, Julián Luengo +1
Transformers have become the leading choice in natural language processing over other deep learning architectures. This trend has also permeated the field of time series analysis,…
A robust approach for deep neural networks in presence of label noise: relabelling and filtering instances during training
Anabel Gómez-Ríos, Julián Luengo, Francisco Herrera
Deep learning has outperformed other machine learning algorithms in a variety of tasks, and as a result, it is widely used. However, like other machine learning algorithms, deep le…
Anomaly Detection in Predictive Maintenance: A New Evaluation Framework for Temporal Unsupervised Anomaly Detection Algorithms
Jacinto Carrasco, Irina Markova, David López +6
The research in anomaly detection lacks a unified definition of what represents an anomalous instance. Discrepancies in the nature itself of an anomaly lead to multiple paradigms o…