Intractable generative models, or simulators, are models for which the likelihood is
unavailable but sampling is possible. Most approaches to parameter inference in this setting …

Efficiently pricing multi-asset options poses a significant challenge in quantitative finance.
The Monte Carlo (MC) method remains the prevalent choice for pricing engines; however, its …

Efficiently pricing multi-asset options poses a significant challenge in quantitative finance.
Fourier methods leverage the regularity properties of the integrand in the Fourier domain to …

METHODOLOGY AND APPLICATION OF VARIATIONAL INFERENCE: A SAMPLING METHOD
AND DENSITY ESTIMATION VIA MAXIMUM MEAN DISCREPANCY BY Y Page 1 …

Efficiently pricing multi-asset options is a challenging problem in computational finance.
Although classical Fourier methods are extremely fast in pricing single asset options …

This study theoretically examines the compression phenomenon of typical discrepancies.
The optimal compression ratio of different discrepancies behaves differently and is related to …

This paper presents a method called sampling-computation-optimization (SCO) to design
batch Bayesian optimization. SCO does not construct new high-dimensional acquisition …

The discrepancy is widely used measurement of the uniformity for a design. While there is
an unreasonable phenomenon: for a uniformly distributed design, its discrepancy is always …

The experimental design for a generalized linear model (GLM) is important but challenging
since the design criterion often depends on model specification including the link function …