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Deep backward schemes for high-dimensional nonlinear PDEs

Mathematics of computation, 2020-07, Vol.89 (324), p.1547-1579

2020

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Nesting Monte Carlo for high-dimensional non-linear PDEs

Monte Carlo methods and applications, 2018-12, Vol.24 (4), p.225-247

Warin, Xavier

2018

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Reservoir optimization and machine learning methods

EURO journal on computational optimization, 2023, Vol.11, p.100068, Article 100068

Warin, Xavier

2023

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Approximation Error Analysis of Some Deep Backward Schemes for Nonlinear PDEs

SIAM journal on scientific computing, 2022-01, Vol.44 (1), p.A28-A56

2022

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Incentives, lockdown, and testing: from Thucydides’ analysis to the COVID-19 pandemic

Journal of mathematical biology, 2022-04, Vol.84 (5), p.37-37, Article 37

2022

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Neural networks-based backward scheme for fully nonlinear PDEs

SN Partial Differential Equations and Applications, 2021-02, Vol.2 (1), Article 16

2021

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Numerical Resolution of McKean-Vlasov FBSDEs Using Neural Networks

Methodology and computing in applied probability, 2022-12, Vol.24 (4), p.2557-2586

2022

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Some non monotone schemes for Hamilton-Jacobi-Bellman equations

ESAIM. Proceedings and surveys, 2019, Vol.65, p.476-497

2019

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A PROBABILISTIC NUMERICAL METHOD FOR FULLY NONLINEAR PARABOLIC PDES

The Annals of applied probability, 2011-08, Vol.21 (4), p.1322-1364

2011

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The GroupMax Neural Network Approximation of Convex Functions

IEEE transaction on neural networks and learning systems, 2024-08, Vol.35 (8), p.11608-11612

Warin, Xavier

2024

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A Regression-Based Monte Carlo Method to Solve Backward Stochastic Differential Equations

The Annals of applied probability, 2005-08, Vol.15 (3), p.2172-2202

2005

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Numerical approximation of BSDEs using local polynomial drivers and branching processes

Monte Carlo methods and applications, 2017-12, Vol.23 (4), p.241-263

2017

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Option valuation and hedging using an asymmetric risk function: asymptotic optimality through fully nonlinear partial differential equations

Finance and stochastics, 2020-07, Vol.24 (3), p.633-675

2020

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Unbiased Monte Carlo estimate of stochastic differential equations expectations

Probability and statistics, 2017, Vol.21, p.56-87

2017

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Rate of Convergence of an Empirical Regression Method for Solving Generalized Backward Stochastic Differential Equations

Bernoulli : official journal of the Bernoulli Society for Mathematical Statistics and Probability, 2006-10, Vol.12 (5), p.889-916

2006

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A common shock model for multidimensional electricity intraday price modelling with application to battery valuation

Quantitative finance, 2024-08, Vol.24 (8), p.1157-1176

2024

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Deep learning for efficient frontier calculation in finance

The journal of computational finance, 2022-06

Warin, Xavier

2022

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Representation Results and Error Estimates for Differential Games with Applications Using Neural Networks

Dynamic games and applications, 2024-10

2024

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Some Non-monotone Schemes for Time Dependent Hamilton–Jacobi–Bellman Equations in Stochastic Control

Journal of scientific computing, 2016-03, Vol.66 (3), p.1122-1147

Warin, Xavier

2016

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Machine Learning for Semi Linear PDEs

Journal of scientific computing, 2019-06, Vol.79 (3), p.1667-1712

2019

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Numerical approximation of general Lipschitz BSDEs with branching processes

ESAIM. Proceedings and surveys, 2019, Vol.65, p.309-329

2019

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Mean-field neural networks: Learning mappings on Wasserstein space

Neural networks, 2023-11, Vol.168, p.380-393

2023

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Fast and Stable Multivariate Kernel Density Estimation by Fast Sum Updating

Journal of computational and graphical statistics, 2019-07, Vol.28 (3), p.596-608

2019

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Variance optimal hedging with application to electricity markets

The journal of computational finance, 2019-12

Warin, Xavier

2019

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Fast multivariate empirical cumulative distribution function with connection to kernel density estimation

Computational statistics & data analysis, 2021-10, Vol.162, p.107267, Article 107267

2021

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Deep backward schemes for high-dimensional nonlinear PDEs

Nesting Monte Carlo for high-dimensional non-linear PDEs

Reservoir optimization and machine learning methods

Approximation Error Analysis of Some Deep Backward Schemes for Nonlinear PDEs

Incentives, lockdown, and testing: from Thucydides’ analysis to the COVID-19 pandemic

Neural networks-based backward scheme for fully nonlinear PDEs

Numerical Resolution of McKean-Vlasov FBSDEs Using Neural Networks

Some non monotone schemes for Hamilton-Jacobi-Bellman equations

A PROBABILISTIC NUMERICAL METHOD FOR FULLY NONLINEAR PARABOLIC PDES

The GroupMax Neural Network Approximation of Convex Functions

A Regression-Based Monte Carlo Method to Solve Backward Stochastic Differential Equations

Numerical approximation of BSDEs using local polynomial drivers and branching processes

Option valuation and hedging using an asymmetric risk function: asymptotic optimality through fully nonlinear partial differential equations

Unbiased Monte Carlo estimate of stochastic differential equations expectations

Rate of Convergence of an Empirical Regression Method for Solving Generalized Backward Stochastic Differential Equations

A common shock model for multidimensional electricity intraday price modelling with application to battery valuation

Deep learning for efficient frontier calculation in finance

Representation Results and Error Estimates for Differential Games with Applications Using Neural Networks

Some Non-monotone Schemes for Time Dependent Hamilton–Jacobi–Bellman Equations in Stochastic Control

Machine Learning for Semi Linear PDEs

Numerical approximation of general Lipschitz BSDEs with branching processes

Mean-field neural networks: Learning mappings on Wasserstein space

Fast and Stable Multivariate Kernel Density Estimation by Fast Sum Updating

Variance optimal hedging with application to electricity markets

Fast multivariate empirical cumulative distribution function with connection to kernel density estimation

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