8 citations · 45 across the 11 of their papers we have counts for
11 papers
Transformer-based conditional generative adversarial network for multivariate time series generation
Abdellah Madane, Mohamed-djallel Dilmi, Florent Forest +3
Conditional generation of time-dependent data is a task that has much interest, whether for data augmentation, scenario simulation, completing missing data, or other purposes. Rece…
A Survey and Implementation of Performance Metrics for Self-Organized Maps
Florent Forest, Mustapha Lebbah, Hanane Azzag +1
Self-Organizing Map algorithms have been used for almost 40 years across various application domains such as biology, geology, healthcare, industry and humanities as an interpretab…
Anomaly Detection for Bivariate Signals
Marie Cottrell, Cynthia Faure, Jérôme Lacaille +1
The anomaly detection problem for univariate or multivariate time series is a critical question in many practical applications as industrial processes control, biological measures,…
Selecting the Number of Clusters with a Stability Trade-off: an Internal Validation Criterion
Alex Mourer, Florent Forest, Mustapha Lebbah +2
Model selection is a major challenge in non-parametric clustering. There is no universally admitted way to evaluate clustering results for the obvious reason that no ground truth i…
Anomaly Detection Based on Confidence Intervals Using SOM with an Application to Health Monitoring
Anastasios Bellas, Charles Bouveyron, Marie Cottrell +1
We develop an application of SOM for the task of anomaly detection and visualization. To remove the effect of exogenous independent variables, we use a correction model which is mo…
Search Strategies for Binary Feature Selection for a Naive Bayes Classifier
Tsirizo Rabenoro, Jérôme Lacaille, Marie Cottrell +1
We compare in this paper several feature selection methods for the Naive Bayes Classifier (NBC) when the data under study are described by a large number of redundant binary indica…
Interpretable Aircraft Engine Diagnostic via Expert Indicator Aggregation
Tsirizo Rabenoro, Jérôme Lacaille, Marie Cottrell +1
Detecting early signs of failures (anomalies) in complex systems is one of the main goal of preventive maintenance. It allows in particular to avoid actual failures by (re)scheduli…
Anomaly Detection Based on Indicators Aggregation
Tsirizo Rabenoro, Jérôme Lacaille, Marie Cottrell +1
Automatic anomaly detection is a major issue in various areas. Beyond mere detection, the identification of the source of the problem that produced the anomaly is also essential. T…
A Methodology for the Diagnostic of Aircraft Engine Based on Indicators Aggregation
Tsirizo Rabenoro, Jérôme Lacaille, Marie Cottrell +1
Aircraft engine manufacturers collect large amount of engine related data during flights. These data are used to detect anomalies in the engines in order to help companies optimize…
Anomaly Detection Based on Aggregation of Indicators
Tsirizo Rabenoro, Jérôme Lacaille, Marie Cottrell +1
Automatic anomaly detection is a major issue in various areas. Beyond mere detection, the identification of the origin of the problem that produced the anomaly is also essential. T…
Fault prediction in aircraft engines using Self-Organizing Maps
Marie Cottrell, Patrice Gaubert, Cédric Eloy +4
Aircraft engines are designed to be used during several tens of years. Their maintenance is a challenging and costly task, for obvious security reasons. The goal is to ensure a pro…