32 citations · 182 across the 41 of their papers we have counts for
47 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…
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…
Online Rolling Controlled Sequential Monte Carlo
Liwen Xue, Axel Finke, Adam M. Johansen
We introduce methodology for real-time inference in general-state-space hidden Markov models. Specifically, we extend recent advances in controlled sequential Monte Carlo (CSMC) me…
Inference for Diffusion Processes via Controlled Sequential Monte Carlo and Splitting Schemes
Shu Huang, Richard G. Everitt, Massimiliano Tamborrino +1
We introduce an inferential framework for a wide class of semi-linear stochastic differential equations (SDEs). Recent work has shown that numerical splitting schemes can preserve…
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…