16 citations · 28 across the 7 of their papers we have counts for
12 papers
Conditional sequential Monte Carlo in high dimensions
Axel Finke, Alexandre H. Thiery
The iterated conditional sequential Monte Carlo (i-CSMC) algorithm from Andrieu, Doucet and Holenstein (2010) is an MCMC approach for efficiently sampling from the joint posterior…
Pretrained equivariant features improve unsupervised landmark discovery
Rahul Rahaman, Atin Ghosh, Alexandre H. Thiery
Locating semantically meaningful landmark points is a crucial component of a large number of computer vision pipelines. Because of the small number of available datasets with groun…
On Data-Augmentation and Consistency-Based Semi-Supervised Learning
Atin Ghosh, Alexandre H. Thiery
Recently proposed consistency-based Semi-Supervised Learning (SSL) methods such as the -model, temporal ensembling, the mean teacher, or the virtual adversarial training, have a…
Towards Label-Free 3D Segmentation of Optical Coherence Tomography Images of the Optic Nerve Head Using Deep Learning
Sripad Krishna Devalla, Tan Hung Pham, Satish Kumar Panda +16
Since the introduction of optical coherence tomography (OCT), it has been possible to study the complex 3D morphological changes of the optic nerve head (ONH) tissues that occur al…
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…