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ORCIDOlivier Schwander
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2020 – today
- 2023
[j4]Thomas Gerald, Hadi Zaatiti, Hatem Hajri, Nicolas Baskiotis, Olivier Schwander:
A hyperbolic approach for learning communities on graphs. Data Min. Knowl. Discov. 37(3): 1090-1124 (2023)- 2022
- [c16]Evangelos Moschos, Alexandre Stegner, Briac Le Vu, Olivier Schwander:
Real-Time Validation of Operational Ocean Models Via Eddy-Decting Deep Neural Networks. IGARSS 2022: 8008-8011 - 2020
- [j3]Evangelos Moschos
, Alexandre Stegner, Olivier Schwander, Patrick Gallinari:
Classification of Eddy Sea Surface Temperature Signatures Under Cloud Coverage. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 13: 3437-3447 (2020) - [c15]Evangelos Moschos, Olivier Schwander, Alexandre Stegner, Patrick Gallinari:
Deep-SST-Eddies: A Deep Learning Framework to Detect Oceanic Eddies in Sea Surface Temperature Images. ICASSP 2020: 4307-4311
2010 – 2019
- 2019
- [c14]Daniel A. Brooks, Olivier Schwander, Frédéric Barbaresco, Jean-Yves Schneider, Matthieu Cord:
Second-Order Networks in PyTorch. GSI 2019: 751-758 - [c13]Tom Véniat, Olivier Schwander, Ludovic Denoyer:
Stochastic Adaptive Neural Architecture Search for Keyword Spotting. ICASSP 2019: 2842-2846 - [c12]Daniel A. Brooks, Olivier Schwander, Frédéric Barbaresco, Jean-Yves Schneider, Matthieu Cord:
Exploring Complex Time-series Representations for Riemannian Machine Learning of Radar Data. ICASSP 2019: 3672-3676 - [c11]Daniel A. Brooks, Olivier Schwander, Frédéric Barbaresco, Jean-Yves Schneider, Matthieu Cord:
Riemannian batch normalization for SPD neural networks. NeurIPS 2019: 15463-15474 - [i2]Daniel A. Brooks, Olivier Schwander, Frédéric Barbaresco, Jean-Yves Schneider, Matthieu Cord:
Riemannian batch normalization for SPD neural networks. CoRR abs/1909.02414 (2019) - 2018
- [j2]Alejandro Lopez Rincon, Alberto Paolo Tonda, Mohamed Elati, Olivier Schwander, Benjamin Piwowarski, Patrick Gallinari:
Evolutionary optimization of convolutional neural networks for cancer miRNA biomarkers classification. Appl. Soft Comput. 65: 91-100 (2018) - [c10]Octave Mariotti, Matthieu Cord, Olivier Schwander:
Exploring deep vision models for acoustic scene classification. DCASE 2018: 103-107 - [i1]Tom Véniat, Olivier Schwander, Ludovic Denoyer:
Stochastic Adaptive Neural Architecture Search for Keyword Spotting. CoRR abs/1811.06753 (2018) - 2016
- [c9]Olivier Schwander, Stéphane Marchand-Maillet, Frank Nielsen:
Comix: Joint estimation and lightspeed comparison of mixture models. ICASSP 2016: 2449-2453 - 2015
- [c8]Olivier Schwander, Frank Nielsen:
Bag-of-Components: An Online Algorithm for Batch Learning of Mixture Models. GSI 2015: 387-395 - 2014
- [c7]Olivier Schwander:
Code You Are Happy to Paste: An Algorithmic Dictionary of Exponential Families. ECML/PKDD (3) 2014: 51-65 - 2013
- [b1]Olivier Schwander:
Méthodes de géométrie de l'information pour les modèles de mélange. (Information-geometric methods for mixture models). École Polytechnique, Palaiseau, France, 2013 - [c6]Olivier Schwander, Frank Nielsen:
Fast Learning of Gamma Mixture Models with k-MLE. SIMBAD 2013: 235-249 - 2012
- [j1]Adelene Y. L. Sim, Olivier Schwander, Michael Levitt, Julie Bernauer:
Evaluating Mixture Models for Building RNA Knowledge-Based Potentials. J. Bioinform. Comput. Biol. 10(2) (2012) - [c5]Olivier Schwander, Frank Nielsen:
Model centroids for the simplification of Kernel Density estimators. ICASSP 2012: 737-740 - [c4]Olivier Schwander, Aurelien J. Schutz, Frank Nielsen, Yannick Berthoumieu:
k-MLE for mixtures of generalized Gaussians. ICPR 2012: 2825-2828 - 2011
- [c3]Olivier Schwander, Frank Nielsen:
Non-flat clustering with alpha-divergences. ICASSP 2011: 2100-2103 - 2010
- [c2]Frank Nielsen, Sylvain Boltz, Olivier Schwander:
Bhattacharyya Clustering with Applications to Mixture Simplifications. ICPR 2010: 1437-1440 - [c1]Olivier Schwander, Frank Nielsen:
Reranking with Contextual Dissimilarity Measures from Representational Bregman k-Means. VISAPP (1) 2010: 118-123
Coauthor Index
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