most citedDeep neural networks algorithms for stochastic control problems on finite horizon: convergence analysis

97 citations · 128 across the 3 of their papers we have counts for

collaborators

3 papers

math.PR2019★ 11 cited

Deep backward schemes for high-dimensional nonlinear PDEs

Côme Huré, Huyên Pham, Xavier Warin

We propose new machine learning schemes for solving high dimensional nonlinear partial differential equations (PDEs). Relying on the classical backward stochastic differential equa…

math.OC2018★ 20 cited

Deep neural networks algorithms for stochastic control problems on finite horizon: numerical applications

Achref Bachouch, Côme Huré, Nicolas Langrené +1

This paper presents several numerical applications of deep learning-based algorithms that have been introduced in [HPBL18]. Numerical and comparative tests using TensorFlow illustr…

math.PR2018★ 97 cited

Deep neural networks algorithms for stochastic control problems on finite horizon: convergence analysis

Côme Huré, Huyên Pham, Achref Bachouch +1

This paper develops algorithms for high-dimensional stochastic control problems based on deep learning and dynamic programming. Unlike classical approximate dynamic programming app…