12 papers
Deep Gaussian Processes on Directed Acyclic Graphs
Federico L. Perlino, Oliver Hamelijnck, Adam M. Johansen +1
Many real-world processes can be represented as compositions of functions along a directed acyclic graph (DAG). In causal modelling, these correspond to the underlying mechanisms;…
Resampling in conditional SMC algorithms
Axel Finke, Adam M. Johansen, Anthony Lee +1
Conditional sequential Monte Carlo (CSMC) algorithms arise in particle Markov chain Monte Carlo and a number of related settings. As in standard sequential Monte Carlo (SMC) algori…
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…
On the Coalescence Time Distribution in Multi-type Supercritical Branching Processes
Janique Krasnowska, Paul Jenkins, Adam Johansen
Consider a population evolving as a discrete-time supercritical multi-type Galton--Watson process. Suppose we run the process for generations, then sample individuals unifo…
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,…