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Found 3 papers, 1 papers with code
Data-driven initialization of deep learning solvers for Hamilton-Jacobi-Bellman PDEs
A deep learning approach for the approximation of the Hamilton-Jacobi-Bellman partial differential equation (HJB PDE) associated to the Nonlinear Quadratic Regulator (NLQR) problem.
Towards Robust and Stable Deep Learning Algorithms for Forward Backward Stochastic Differential Equations
Applications in quantitative finance such as optimal trade execution, risk management of options, and optimal asset allocation involve the solution of high dimensional and nonlinear Partial Differential Equations (PDEs).
Combination of multiple Deep Learning architectures for Offensive Language Detection in Tweets
This report contains the details regarding our submission to the OffensEval 2019 (SemEval 2019 - Task 6).
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