3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2023
Derivative-based Shapley value for global sensitivity analysis and machine learning explainability
Hui Duan, Giray Ökten
We introduce a new Shapley value approach for global sensitivity analysis and machine learning explainability. The method is based on the first-order partial derivatives of the und…
q-fin.CP2014
High Performance Financial Simulation Using Randomized Quasi-Monte Carlo Methods
Linlin Xu, Giray Ökten
GPU computing has become popular in computational finance and many financial institutions are moving their CPU based applications to the GPU platform. Since most Monte Carlo algori…
q-fin.CP2014★ 3 cited
The acceptance-rejection method for low-discrepancy sequences
Nguyet Nguyen, Giray Ökten
Generation of pseudorandom numbers from different probability distributions has been studied extensively in the Monte Carlo simulation literature. Two standard generation technique…