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09/08/2023
Actor critic learning algorithms for mean-field control with moment neural networks
We develop a new policy gradient and actor-critic algorithm for solving ...
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07/31/2023
A Common Shock Model for multidimensional electricity intraday price modelling with application to battery valuation
In this paper, we propose a multidimensional statistical model of intrad...
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03/20/2023
Quantile and moment neural networks for learning functionals of distributions
We study news neural networks to approximate function of distributions i...
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12/22/2022
Mean-field neural networks-based algorithms for McKean-Vlasov control problems *
This paper is devoted to the numerical resolution of McKean-Vlasov contr...
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10/27/2022
Mean-field neural networks: learning mappings on Wasserstein space
We study the machine learning task for models with operators mapping bet...
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05/07/2020
Fast multivariate empirical cumulative distribution function with connection to kernel density estimation
This paper revisits the problem of computing empirical cumulative distri...
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02/07/2020
Discretization and Machine Learning Approximation of BSDEs with a Constraint on the Gains-Process
We study the approximation of backward stochastic differential equations...
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07/31/2019
Neural networks-based backward scheme for fully nonlinear PDEs
We propose a numerical method for solving high dimensional fully nonline...
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02/05/2019
Some machine learning schemes for high-dimensional nonlinear PDEs
We propose new machine learning schemes for solving high dimensional non...
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09/20/2018
Machine Learning for semi linear PDEs
Recent machine learning algorithms dedicated to solving semi-linear PDEs...
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12/04/2017