Patrimony

The Louis Bachelier Group's patrimony has been defined as all the publications produced by academic researchers thanks to Group funding (ILB, FdR, IEF, Labex) or via the use of EquipEx data (BEDOFIH, EUROFIDAI).


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New methods for image classification, image retrieval and semantic correspondence.

Correspondance de région, Correspondance sémantique, Fisher vectors, Image representation, Image retrieval, Kernel methods, Modèle à noyaux, Neural networks, Recherche d’image, Region matching, Représentation d’image, Réseau de neurones, Semantic matching, Vecteurs de Fisher

Some results on the McKean–Vlasov optimal control and mean field games : Limit theorems, dynamic programming principle and numerical approximations.

Approximations numériques, Jeux à champ moyen, McKean--Vlasov equations, Mean field game, Nash equilibria, Neural networks, Numerical approximation, Pareto equilibria, Problème de contrôle stochastique, Réseaux de neurones, Stochastic control problem, Stochastic differential equation, Équation différentielle stochastique, Équations de McKean--Vlasov, Équilibres de Nash, Équilibres de Pareto

Tail-GAN: Simulation of extreme events with ReLU neural networks.

Extreme Value Theory, Generative models, Neural networks

On the approximation of extreme quantiles with neural networks.

Extreme value theory, Generative models, Modèle génératif, Neural networks, Réseau de neurones, Théorie des valeurs extrêmes

Generative model for fBm with deep ReLU neural networks.

Fractional Brownian motion, Gaussian process, Generative models, Neural networks

Modeling and optimal strategies in short-term energy markets.

Contrôle optimal, Energies renouvelables, Energy markets, Machine learning, Marché des services systèmes, Marchés de l’énergie, Neural networks, Optimal control, Renewable energies, Réseau de neurones, System services market

Neural network regression for Bermudan option pricing.

Bermudan options, Deep learning, Neural networks, Optimal stopping, Regression methods

Modeling and optimal strategies in short-term energy markets.

Contrôle optimal, Energies renouvelables, Energy markets, Machine learning, Marché des services systèmes, Marchés de l’énergie, Neural networks, Optimal control, Renewable energies, Réseau de neurones, System services market

Numerical resolution of McKean-Vlasov FBSDEs using neural networks *.

Deep BSDE, Machine learning, McKean-Vlasov FBSDEs, Mean-field games, Neural networks

Deep backward multistep schemes for nonlinear PDEs and approximation error analysis.

Backward SDEs, Error estimates, Malliavin weights, Multistep schemes, Neural networks, Nonlinear PDEs, Numerical approximation

Input noise injection for supervised machine learning, with applications on genomic and image data.

Apprentissage statistique, Bioinformatics, Bioinformatique, Bruit, Deep learning, Dropout, Machine learning, Neural networks, Noise injection, Régularisation, Réseau de neurones

NDR: Noise and Dimensionality Reduction of CSI for Indoor Positioning Using Deep Learning.

CSI, Channel state information, Deep learning, Indoor localization, MIMO, Neural networks