166 citations · 309 across the 26 of their papers we have counts for
7 papers · 1 filter
Manifold Markov chain Monte Carlo methods for Bayesian inference in diffusion models
Matthew M. Graham, Alexandre H. Thiery, Alexandros Beskos
Bayesian inference for nonlinear diffusions, observed at discrete times, is a challenging task that has prompted the development of a number of algorithms, mainly within the comput…
DeshadowGAN: A Deep Learning Approach to Remove Shadows from Optical Coherence Tomography Images
Haris Cheong, Sripad Krishna Devalla, Tan Hung Pham +9
Purpose: To remove retinal shadows from optical coherence tomography (OCT) images of the optic nerve head(ONH). Methods:2328 OCT images acquired through the center of the ONH using…
Sequential Ensemble Transform for Bayesian Inverse Problems
Aaron Myers, Alexandre H. Thiery, Kainan Wang +1
We present the Sequential Ensemble Transform (SET) method, an approach for generating approximate samples from a Bayesian posterior distribution. The method explores the posterior…
Deep Learning Algorithms to Isolate and Quantify the Structures of the Anterior Segment in Optical Coherence Tomography Images
Tan Hung Pham, Sripad Krishna Devalla, Aloysius Ang +6
Accurate isolation and quantification of intraocular dimensions in the anterior segment (AS) of the eye using optical coherence tomography (OCT) images is important in the diagnosi…
On importance-weighted autoencoders
Axel Finke, Alexandre H. Thiery
The importance weighted autoencoder (IWAE) (Burda et al., 2016) is a popular variational-inference method which achieves a tighter evidence bound (and hence a lower bias) than stan…
A scalable optimal-transport based local particle filter
Matthew M. Graham, Alexandre H. Thiery
Filtering in spatially-extended dynamical systems is a challenging problem with significant practical applications such as numerical weather prediction. Particle filters allow asym…
Particle filter efficiency under limited communication
Deborshee Sen
Sequential Monte Carlo methods are typically not straightforward to implement on parallel architectures. This is because standard resampling schemes involve communication between a…