32 citations · 182 across the 41 of their papers we have counts for
6 papers · 1 filter
Redesigning the ensemble Kalman filter with a dedicated model of epistemic uncertainty
Chatchuea Kimchaiwong, Jeremie Houssineau, Adam M. Johansen
The problem of incorporating information from observations received serially in time is widespread in the field of uncertainty quantification. Within a probabilistic framework, suc…
Solving Fredholm Integral Equations of the Second Kind via Wasserstein Gradient Flows
Francesca R. Crucinio, Adam M. Johansen
Motivated by a recent method for approximate solution of Fredholm equations of the first kind, we develop a corresponding method for a class of Fredholm equations of the \emph{seco…
Fast convergence of the Expectation Maximization algorithm under a logarithmic Sobolev inequality
Rocco Caprio, Adam M Johansen
We present a new framework for analysing the Expectation Maximization (EM) algorithm. Drawing on recent advances in the theory of gradient flows over Euclidean-Wasserstein spaces,…
Particle Semi-Implicit Variational Inference
Jen Ning Lim, Adam M. Johansen
Semi-implicit variational inference (SIVI) enriches the expressiveness of variational families by utilizing a kernel and a mixing distribution to hierarchically define the variatio…
Genealogical processes of sequential Monte Carlo methods and other non-neutral population models under rapid mutation
Jere Koskela, Paul A. Jenkins, Adam M. Johansen +1
We show that genealogical trees arising from a broad class of non-neutral models of population evolution converge to the Kingman coalescent under a suitable rescaling of time. As w…
Error bounds for particle gradient descent, and extensions of the log-Sobolev and Talagrand inequalities
Rocco Caprio, Juan Kuntz, Samuel Power +1
We prove non-asymptotic error bounds for particle gradient descent (PGD, Kuntz et al., 2023), a recently introduced algorithm for maximum likelihood estimation of large latent vari…