Bhattacharyya Clustering with Applications to Mixture Simplifications. - Frank Nielsen; Sylvain Boltz; Olivier Schwander (ICPR, 2010)

Reranking with Contextual Dissimilarity Measures from Representational Bregman k-Means. - Olivier Schwander; Frank Nielsen (VISAPP (1), 2010)

Non-flat clustering with alpha-divergences. - Olivier Schwander; Frank Nielsen (ICASSP, 2011)

Model centroids for the simplification of Kernel Density estimators. - Olivier Schwander; Frank Nielsen (ICASSP, 2012)

k-MLE for mixtures of generalized Gaussians. - Olivier Schwander; Aurelien J. Schutz; Frank Nielsen; Yannick Berthoumieu (ICPR, 2012)

Evaluating Mixture Models for Building RNA Knowledge-Based Potentials. - Adelene Y. L. Sim; Olivier Schwander; Michael Levitt 001; Julie Bernauer (J. Bioinform. Comput. Biol., 2012)

Fast Learning of Gamma Mixture Models with k-MLE. - Olivier Schwander; Frank Nielsen (SIMBAD, 2013)

Méthodes de géométrie de l'information pour les modèles de mélange. (Information-geometric methods for mixture models). - Olivier Schwander (2013)

Code You Are Happy to Paste: An Algorithmic Dictionary of Exponential Families. - Olivier Schwander (ECML/PKDD (3), 2014)

Bag-of-Components: An Online Algorithm for Batch Learning of Mixture Models. - Olivier Schwander; Frank Nielsen (GSI, 2015)

Comix: Joint estimation and lightspeed comparison of mixture models. - Olivier Schwander; Stéphane Marchand-Maillet; Frank Nielsen (ICASSP, 2016)

Exploring deep vision models for acoustic scene classification. - Octave Mariotti; Matthieu Cord; Olivier Schwander (DCASE, 2018)

Evolutionary optimization of convolutional neural networks for cancer miRNA biomarkers classification. - Alejandro Lopez Rincon; Alberto Paolo Tonda; Mohamed Elati; Olivier Schwander; Benjamin Piwowarski; Patrick Gallinari (Appl. Soft Comput., 2018)

Second-Order Networks in PyTorch. - Daniel A. Brooks; Olivier Schwander; Frédéric Barbaresco; Jean-Yves Schneider; Matthieu Cord (GSI, 2019)

Exploring Complex Time-series Representations for Riemannian Machine Learning of Radar Data. - Daniel A. Brooks; Olivier Schwander; Frédéric Barbaresco; Jean-Yves Schneider; Matthieu Cord (ICASSP, 2019)

Stochastic Adaptive Neural Architecture Search for Keyword Spotting. - Tom Véniat; Olivier Schwander; Ludovic Denoyer (ICASSP, 2019)

Riemannian batch normalization for SPD neural networks. - Daniel A. Brooks; Olivier Schwander; Frédéric Barbaresco; Jean-Yves Schneider; Matthieu Cord (NeurIPS, 2019)

Deep-SST-Eddies: A Deep Learning Framework to Detect Oceanic Eddies in Sea Surface Temperature Images. - Evangelos Moschos; Olivier Schwander; Alexandre Stegner; Patrick Gallinari (ICASSP, 2020)

Classification of Eddy Sea Surface Temperature Signatures Under Cloud Coverage. - Evangelos Moschos; Alexandre Stegner; Olivier Schwander; Patrick Gallinari (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2020)

Real-Time Validation of Operational Ocean Models Via Eddy-Decting Deep Neural Networks. - Evangelos Moschos; Alexandre Stegner; Briac Le Vu; Olivier Schwander (IGARSS, 2022)

A hyperbolic approach for learning communities on graphs. - Thomas Gerald; Hadi Zaatiti; Hatem Hajri; Nicolas Baskiotis; Olivier Schwander (Data Min. Knowl. Discov., 2023)