22 citations · 29 across the 6 of their papers we have counts for
6 papers
Neural Networks with Local Converging Inputs for Efficient Options Pricing Models
Harris Cobb, Wenbo Hao, Yingjie Liu
We present a novel application of Neural Networks with Local Converging Inputs (NNLCI) to improve the efficiency of existing numerical methods for pricing multi-asset options. The…
Group projected Subspace Pursuit for Identification of variable coefficient differential equations (GP-IDENT)
Yuchen He, Sung-Ha Kang, Wenjing Liao +2
We propose an effective and robust algorithm for identifying partial differential equations (PDEs) with space-time varying coefficients from a single trajectory of noisy observatio…
Solving Maxwell's Equation in 2D with Neural Networks with Local Converging Inputs
Harris Cobb, Hwi Lee, Yingjie Liu
In this paper we apply neural networks with local converging inputs (NNLCI), originally introduced in [arXiv:2109.09316], to solve the two dimensional Maxwell's equation around per…
Numerical Identification of Nonlocal Potential in Aggregation
Yuchen He, Sung Ha Kang, Wenjing Liao +2
Aggregation equations are broadly used to model population dynamics with nonlocal interactions, characterized by a potential in the equation. This paper considers the inverse probl…
Robust Identification of Differential Equations by Numerical Techniques from a Single Set of Noisy Observation
Yuchen He, Sung Ha Kang, Wenjing Liao +2
We propose robust methods to identify underlying Partial Differential Equation (PDE) from a given set of noisy time dependent data. We assume that the governing equation is a linea…
IDENT: Identifying Differential Equations with Numerical Time evolution
Sung Ha Kang, Wenjing Liao, Yingjie Liu
Identifying unknown differential equations from a given set of discrete time dependent data is a challenging problem. A small amount of noise can make the recovery unstable, and no…