9 citations · 10 across the 4 of their papers we have counts for
4 papers
Particle-MALA and Particle-mGRAD: Gradient-based MCMC methods for high-dimensional state-space models
Adrien Corenflos, Axel Finke
State-of-the-art methods for Bayesian inference in state-space models are (a) conditional sequential Monte Carlo (CSMC) algorithms; (b) sophisticated 'classical' MCMC algorithms li…
Neural-based Cross-modal Search and Retrieval of Artwork
Yan Gong, Georgina Cosma, Axel Finke
Creating an intelligent search and retrieval system for artwork images, particularly paintings, is crucial for documenting cultural heritage, fostering wider public engagement, and…
Identifying Early Help Referrals For Local Authorities With Machine Learning And Bias Analysis
Eufrásio de A. Lima Neto, Jonathan Bailiss, Axel Finke +2
Local authorities in England, such as Leicestershire County Council (LCC), provide Early Help services that can be offered at any point in a young person's life when they experienc…
On embedded hidden Markov models and particle Markov chain Monte Carlo methods
Axel Finke, Arnaud Doucet, Adam M. Johansen
The embedded hidden Markov model (EHMM) sampling method is a Markov chain Monte Carlo (MCMC) technique for state inference in non-linear non-Gaussian state-space models which was p…