Non-linear Analysis of Shocks when Financial Markets are Subject to Changes in Regime. - Bertrand Maillet; Madalina Olteanu; Joseph Rynkiewicz (ESANN, 2004)

A descriptive method to evaluate the number of regimes in a switching autoregressive model. - Madalina Olteanu (Neural Networks, 2006)

Mixing Kohonen Algorithm, Markov Switching Model and Detection of Multiple Change-Points: An Application to Monetary History. - Marie-Thérèse Boyer-Xambeu; Ghislain Deleplace; Patrice Gaubert; Lucien Gillard; Madalina Olteanu (IWANN, 2007)

Estimating the number of components in a mixture of multilayer perceptrons. - Madalina Olteanu; Joseph Rynkiewicz (Neurocomputing, 2008)

Supervised classification of categorical data with uncertain labels for DNA barcoding. - Charles Bouveyron; Stéphane Girard; Madalina Olteanu (ESANN, 2009)

Modelling Dengue Epidemics with Autoregressive Switching Markov Models (AR-HMM). - Madalina Olteanu; Esther García-Garaluz; Miguel A. Atencia Ruiz; Gonzalo Joya Caparrós (IWANN (1), 2009)

Career-Path Analysis Using Optimal Matching and Self-Organizing Maps. - Sébastien Massoni; Madalina Olteanu; Patrick Rousset (WSOM, 2009)

DNA barcode analysis: a comparison of phylogenetic and statistical classification methods. - Frederic Austerlitz; Olivier David; Brigitte Schaeffer; Kevin Bleakley; Madalina Olteanu; Raphaël Leblois; Michel Veuille; Catherine Larédo (BMC Bioinform., 2009)

Asymptotic properties of mixture-of-experts models. - Madalina Olteanu; Joseph Rynkiewicz (Neurocomputing, 2011)

Hidden Markov models for time series of counts with excess zeros. - Madalina Olteanu; James Ridgway (ESANN, 2012)

On-Line Relational SOM for Dissimilarity Data. - Madalina Olteanu; Nathalie Villa-Vialaneix; Marie Cottrell (WSOM, 2012)

Neural Networks for Complex Data. - Marie Cottrell; Madalina Olteanu; Fabrice Rossi; Joseph Rynkiewicz; Nathalie Villa-Vialaneix (Künstliche Intell., 2012)

Multiple Kernel Self-Organizing Maps. - Madalina Olteanu; Nathalie Villa-Vialaneix; Christine Cierco-Ayrolles (ESANN, 2013)

Which Dissimilarity Is to Be Used When Extracting Typologies in Sequence Analysis? A Comparative Study. - Sébastien Massoni; Madalina Olteanu; Nathalie Villa-Vialaneix (IWANN (1), 2013)

SOMbrero: An R Package for Numeric and Non-numeric Self-Organizing Maps. - Julien Boelaert; Laura Bendhaiba; Madalina Olteanu; Nathalie Villa-Vialaneix (WSOM, 2014)

Bagged Kernel SOM. - Jérôme Mariette; Madalina Olteanu; Julien Boelaert; Nathalie Villa-Vialaneix (WSOM, 2014)

Search for Meaning Through the Study of Co-occurrences in Texts. - Nicolas Bourgeois; Marie Cottrell; Stéphane Lamassé; Madalina Olteanu (IWANN (2), 2015)

On-line relational and multiple relational SOM. - Madalina Olteanu; Nathalie Villa-Vialaneix (Neurocomputing, 2015)

Comparison of three algorithms for parametric change-point detection. - Cynthia Faure; Jean-Marc Bardet; Madalina Olteanu; Jérôme Lacaille (ESANN, 2016)

Theoretical and Applied Aspects of the Self-Organizing Maps. - Marie Cottrell; Madalina Olteanu; Fabrice Rossi; Nathalie Villa-Vialaneix (WSOM, 2016)

Sparse Online Self-Organizing Maps for Large Relational Data. - Madalina Olteanu; Nathalie Villa-Vialaneix (WSOM, 2016)

Accelerating stochastic kernel SOM. - Jérôme Mariette; Fabrice Rossi; Madalina Olteanu; Nathalie Villa-Vialaneix (ESANN, 2017)

Hidden-Markov Models for Time Series of Continuous Proportions with Excess Zeros. - Julien Alerini; Marie Cottrell; Madalina Olteanu (IWANN (2), 2017)

Multidimensional urban segregation: An exploratory case study. - Marie Cottrell; Madalina Olteanu; Julien Randon-Furling; Aurélien Hazan (WSOM, 2017)

Using self-organizing maps for clustering anc labelling aircraft engine data phases. - Cynthia Faure; Madalina Olteanu; Jean-Marc Bardet; Jérôme Lacaille (WSOM, 2017)

Efficient interpretable variants of online SOM for large dissimilarity data. - Jérôme Mariette; Madalina Olteanu; Nathalie Villa-Vialaneix (Neurocomputing, 2017)

Analyzing spatial dissimilarities in high-resolution geo-data : a case study of four European cities. - Julien Randon-Furling; William Clark; Madalina Olteanu (ESANN, 2019)

Anomaly Detection for Bivariate Signals. - Marie Cottrell; Cynthia Faure; Jérôme Lacaille; Madalina Olteanu (IWANN (1), 2019)

Detection of Abnormal Flights Using Fickle Instances in SOM Maps. - Marie Cottrell; Cynthia Faure; Jérôme Lacaille; Madalina Olteanu (WSOM+, 2019)

When Clustering the Multiscalar Fingerprint of the City Reveals Its Segregation Patterns. - Madalina Olteanu; Jean-Charles Lamirel (WSOM+, 2019)

Sparse K-means for mixed data via group-sparse clustering. - Marie Chavent; Jérôme Lacaille; Alex Mourer; Madalina Olteanu (ESANN, 2020)

Editorial. - Jean-Charles Lamirel; Marie Cottrell; Madalina Olteanu; Bruno Lévy 001 (Neural Comput. Appl., 2020)

Multidimensional urban segregation: toward a neural network measure. - Madalina Olteanu; Aurélien Hazan; Marie Cottrell; Julien Randon-Furling (Neural Comput. Appl., 2020)

Handling Correlations in Random Forests: which Impacts on Variable Importance and Model Interpretability? - Marie Chavent; Jérôme Lacaille; Alex Mourer; Madalina Olteanu (ESANN, 2021)

Challenges in anomaly and change point detection. - Madalina Olteanu; Fabrice Rossi; Florian Yger (ESANN, 2022)

Meta-survey on outlier and anomaly detection. - Madalina Olteanu; Fabrice Rossi; Florian Yger (Neurocomputing, 2023)

Sparse Clustering with K-Means - Which Penalties and for Which Data? - Marie Chavent; Marie Cottrell; Alex Mourer; Madalina Olteanu (WSOM+, 2024)