Computer modeling of isothermal crystallization in short fiber reinforced composites. - Chunlei Ruan; Jie Ouyang; Shuaiqiang Liu; Lin Zhang 010 (Comput. Chem. Eng., 2011)

Pricing options and computing implied volatilities using neural networks. - Shuaiqiang Liu; Cornelis W. Oosterlee; Sander M. Bohté (CoRR, 2019)

A neural network-based framework for financial model calibration. - Shuaiqiang Liu; Anastasia Borovykh; Lech A. Grzelak; Cornelis W. Oosterlee (CoRR, 2019)

On Calibration Neural Networks for extracting implied information from American options. - Shuaiqiang Liu; Álvaro Leitao; Anastasia Borovykh; Cornelis W. Oosterlee (CoRR, 2020)

The Seven-League Scheme: Deep learning for large time step Monte Carlo simulations of stochastic differential equations. - Shuaiqiang Liu; Lech A. Grzelak; Cornelis W. Oosterlee (CoRR, 2020)

Monte Carlo Simulation of SDEs using GANs. - Jorino van Rhijn; Cornelis W. Oosterlee; Lech A. Grzelak; Shuaiqiang Liu (CoRR, 2021)

Solution of integrals with fractional Brownian motion for different Hurst indices. - Fei Gao; Shuaiqiang Liu; Cornelis W. Oosterlee; Nico M. Temme (CoRR, 2022)

GPU acceleration of the Seven-League Scheme for large time step simulations of stochastic differential equations. - Shuaiqiang Liu; Graziana Colonna; Lech A. Grzelak; Cornelis W. Oosterlee (CoRR, 2023)

Evaluation of integrals with fractional Brownian motion for different Hurst indices. - Fei Gao; Shuaiqiang Liu; Cornelis W. Oosterlee; Nico M. Temme (Int. J. Comput. Math., 2023)

Improved model-free bounds for multi-asset options using option-implied information and deep learning. - Evangelia Dragazi; Shuaiqiang Liu; Antonis Papapantoleon (CoRR, 2024)