research
∙
08/31/2023
Model Selection for Ordinary Differential Equations: a Statistical Testing Approach
Ordinary differential equations (ODEs) are foundational in modeling intr...
share
research
∙
11/16/2020
Nonparametric Bayesian volatility estimation for gamma-driven stochastic differential equations
We study a nonparametric Bayesian approach to estimation of the volatili...
research
∙
08/10/2019
Separable nonlinear least-squares parameter estimation for complex dynamic systems
Nonlinear dynamic models are widely used for characterizing functional f...
research
∙
03/26/2019
Decompounding discrete distributions: A non-parametric Bayesian approach
Suppose that a compound Poisson process is observed discretely in time a...
research
∙
10/17/2018
Bayesian wavelet de-noising with the caravan prior
According to both domain expertise knowledge and empirical evidence, wav...
research
∙
05/15/2018
Nonparametric Bayesian volatility learning under microstructure noise
Aiming at financial applications, we study the problem of learning the v...
research
∙
04/30/2018
Nonparametric Bayesian inference for Lévy subordinators
Given discrete time observations over a growing time interval, we consid...
research
∙
04/10/2018
Fast and scalable non-parametric Bayesian inference for Poisson point processes
We study the problem of non-parametric Bayesian estimation of the intens...
research
∙
02/25/2018
Bayesian inverse problems with partial observations
We study a nonparametric Bayesian approach to linear inverse problems un...
research
∙
02/25/2018
Bayesian linear inverse problems in regularity scales
We obtain rates of contraction of posterior distributions in inverse pro...
research
∙
01/30/2018