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06/28/2023
On the surprising effectiveness of a simple matrix exponential derivative approximation, with application to global SARS-CoV-2
The continuous-time Markov chain (CTMC) is the mathematical workhorse of...
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02/02/2023
Long-term accuracy of numerical approximations of SPDEs with the stochastic Navier-Stokes equations as a paradigm
This work introduces a general framework for establishing the long time ...
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12/06/2022
A Statistical Framework for Domain Shape Estimation in Stokes Flows
We develop and implement a Bayesian approach for the estimation of the s...
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09/10/2022
Parallel MCMC Algorithms: Theoretical Foundations, Algorithm Design, Case Studies
Parallel Markov Chain Monte Carlo (pMCMC) algorithms generate clouds of ...
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06/14/2021
Embracing Uncertainty in "Small Data" Problems: Estimating Earthquakes from Historical Anecdotes
We apply the Bayesian inversion process to make principled estimates of ...
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11/09/2020
On the accept-reject mechanism for Metropolis-Hastings algorithms
This work develops a powerful and versatile framework for determining ac...
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03/17/2020
Mixing Rates for Hamiltonian Monte Carlo Algorithms in Finite and Infinite Dimensions
We establish the geometric ergodicity of the preconditioned Hamiltonian ...
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09/13/2018
