Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: 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). The
connection between PDEs and systems of Forward-Backward Stochastic Differential
Equations (FBSDEs) enables the use of advanced simulation techniques to be
applied even in the high dimensional setting. Unfortunately, when the
underlying application contains nonlinear terms, then classical methods both
for simulation and numerical methods for PDEs suffer from the curse of
dimensionality. Inspired by the success of deep learning, several researchers
have recently proposed to address the solution of FBSDEs using deep learning.
We discuss the dynamical systems point of view of deep learning and compare
several architectures in terms of stability, generalization, and robustness. In
order to speed up the computations, we propose to use a multilevel
discretization technique. Our preliminary results suggest that the multilevel
discretization method improves solutions times by an order of magnitude
compared to existing methods without sacrificing stability or robustness.

24
The categories of this paper are: dg-ga
22
The categories of this paper are: chao-dyn
20
The categories of this paper are: acc-phys
3
The categories of this paper are: physics
27
The categories of this paper are: comp-gas
15
The categories of this paper are: nucl-ex
11
The categories of this paper are: hep-lat
8
The categories of this paper are: hep-ex
31
The categories of this paper are: ao-sci
34
The categories of this paper are: chem-ph
10
The categories of this paper are: q-bio
26
The categories of this paper are: bayes-an
37
The categories of this paper are: supr-con
17
The categories of this paper are: q-fin
2
The categories of this paper are: math
33
The categories of this paper are: plasm-ph