Zobrazeno 1 - 10
of 100
pro vyhledávání: '"Thiery, Alexandre H."'
Autor:
Wang, Chao, Thiery, Alexandre H.
Publikováno v:
Inverse Problems, 2024
Proper regularization is crucial in inverse problems to achieve high-quality reconstruction, even with an ill-conditioned measurement system. This is particularly true for three-dimensional photoacoustic tomography, which is computationally demanding
Externí odkaz:
http://arxiv.org/abs/2409.16564
Out-of-distribution (OOD) detection is a critical task in machine learning that seeks to identify abnormal samples. Traditionally, unsupervised methods utilize a deep generative model for OOD detection. However, such approaches necessitate a differen
Externí odkaz:
http://arxiv.org/abs/2405.11881
We propose an adaptive importance sampling scheme for Gaussian approximations of intractable posteriors. Optimization-based approximations like variational inference can be too inaccurate while existing Monte Carlo methods can be too slow. Therefore,
Externí odkaz:
http://arxiv.org/abs/2404.18556
Autor:
Braeu, Fabian A., Chuangsuwanich, Thanadet, Tun, Tin A., Perera, Shamira A., Husain, Rahat, Kadziauskiene, Aiste, Schmetterer, Leopold, Thiéry, Alexandre H., Barbastathis, George, Aung, Tin, Girard, Michaël J. A.
$\bf{Purpose}$: To describe the 3D structural changes in both connective and neural tissues of the optic nerve head (ONH) that occur concurrently at different stages of glaucoma using traditional and AI-driven approaches. $\bf{Methods}$: We included
Externí odkaz:
http://arxiv.org/abs/2301.02837
Autor:
Braeu, Fabian A., Chuangsuwanich, Thanadet, Tun, Tin A., Thiery, Alexandre H., Aung, Tin, Barbastathis, George, Girard, Michaël J. A.
$\mathbf{Purpose}$: To use artificial intelligence (AI) to: (1) exploit biomechanical knowledge of the optic nerve head (ONH) from a relatively large population; (2) assess ONH robustness from a single optical coherence tomography (OCT) scan of the O
Externí odkaz:
http://arxiv.org/abs/2206.04689
Publikováno v:
ICML 2023
This paper is concerned with online filtering of discretely observed nonlinear diffusion processes. Our approach is based on the fully adapted auxiliary particle filter, which involves Doob's $h$-transforms that are typically intractable. We propose
Externí odkaz:
http://arxiv.org/abs/2206.03369
Purpose: (1) To assess the performance of geometric deep learning (PointNet) in diagnosing glaucoma from a single optical coherence tomography (OCT) 3D scan of the optic nerve head (ONH); (2) To compare its performance to that obtained with a standar
Externí odkaz:
http://arxiv.org/abs/2204.07004
Autor:
Braeu, Fabian A., Thiéry, Alexandre H., Tun, Tin A., Kadziauskiene, Aiste, Barbastathis, George, Aung, Tin, Girard, Michaël J. A.
Purpose: The optic nerve head (ONH) undergoes complex and deep 3D morphological changes during the development and progression of glaucoma. Optical coherence tomography (OCT) is the current gold standard to visualize and quantify these changes, howev
Externí odkaz:
http://arxiv.org/abs/2204.06931
In this paper, we propose an explainable and interpretable diabetic retinopathy (ExplainDR) classification model based on neural-symbolic learning. To gain explainability, a highlevel symbolic representation should be considered in decision making. S
Externí odkaz:
http://arxiv.org/abs/2204.00624
Autor:
Girard, Michaël J. A., Panda, Satish K., Tun, Tin Aung, Wibroe, Elisabeth A., Najjar, Raymond P., Tin, Aung, Thiéry, Alexandre H., Hamann, Steffen, Fraser, Clare, Milea, Dan
Purpose: (1) To develop a deep learning algorithm to identify major tissue structures of the optic nerve head (ONH) in 3D optical coherence tomography (OCT) scans; (2) to exploit such information to robustly differentiate among healthy, optic disc dr
Externí odkaz:
http://arxiv.org/abs/2112.09970