Zobrazeno 1 - 10
of 143
pro vyhledávání: '"Thiery, Alexandre P."'
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
Autor:
Chuangsuwanich, Thanadet, Nongpiur, Monisha E., Braeu, Fabian A., Tun, Tin A., Thiery, Alexandre, Perera, Shamira, Ho, Ching Lin, Buist, Martin, Barbastathis, George, Aung, Tin, Girard, Michaël J. A.
Objective. (1) To assess whether neural tissue structure and biomechanics could predict functional loss in glaucoma; (2) To evaluate the importance of biomechanics in making such predictions. Design, Setting and Participants. We recruited 238 glaucom
Externí odkaz:
http://arxiv.org/abs/2406.14988
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 require a new model to
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
The Gaussian process state-space models (GPSSMs) represent a versatile class of data-driven nonlinear dynamical system models. However, the presence of numerous latent variables in GPSSM incurs unresolved issues for existing variational inference app
Externí odkaz:
http://arxiv.org/abs/2312.05910
Autor:
Wang, Chao, Thiery, Alexandre Hoang
Publikováno v:
Transactions on Machine Learning Research (05 Dec 2023)
This article introduces GIT-Net, a deep neural network architecture for approximating Partial Differential Equation (PDE) operators, inspired by integral transform operators. GIT-NET harnesses the fact that differential operators commonly used for de
Externí odkaz:
http://arxiv.org/abs/2312.02450
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:
Chiang, Charis Y. N., Braeu, Fabian, Chuangsuwanich, Thanadet, Tan, Royston K. Y., Chua, Jacqueline, Schmetterer, Leopold, Thiery, Alexandre, Buist, Martin, Girard, Michaël J. A.
Purpose: (1) To develop a deep learning algorithm to automatically segment structures of the optic nerve head (ONH) and macula in 3D wide-field optical coherence tomography (OCT) scans; (2) To assess whether 3D macula or ONH structures (or the combin
Externí odkaz:
http://arxiv.org/abs/2210.06664
In temporal action segmentation, Timestamp supervision requires only a handful of labelled frames per video sequence. For unlabelled frames, previous works rely on assigning hard labels, and performance rapidly collapses under subtle violations of th
Externí odkaz:
http://arxiv.org/abs/2207.10137
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