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09/04/2023
Towards frugal unsupervised detection of subtle abnormalities in medical imaging
Anomaly detection in medical imaging is a challenging task in contexts w...
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08/23/2023
Anisotropic Hybrid Networks for liver tumor segmentation with uncertainty quantification
The burden of liver tumors is important, ranking as the fourth leading c...
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07/28/2023
Multi-layer Aggregation as a key to feature-based OOD detection
Deep Learning models are easily disturbed by variations in the input ima...
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07/28/2023
TriadNet: Sampling-free predictive intervals for lesional volume in 3D brain MR images
The volume of a brain lesion (e.g. infarct or tumor) is a powerful indic...
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05/26/2023
Semantic segmentation of sparse irregular point clouds for leaf/wood discrimination
LiDAR (Light Detection and Ranging) has become an essential part of the ...
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02/27/2023
Brain subtle anomaly detection based on auto-encoders latent space analysis : application to de novo parkinson patients
Neural network-based anomaly detection remains challenging in clinical a...
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11/10/2022
Improving Uncertainty-based Out-of-Distribution Detection for Medical Image Segmentation
Deep Learning models are easily disturbed by variations in the input ima...
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10/05/2022
Trustworthy clinical AI solutions: a unified review of uncertainty quantification in deep learning models for medical image analysis
The full acceptance of Deep Learning (DL) models in the clinical field i...
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09/22/2022
Beyond Voxel Prediction Uncertainty: Identifying brain lesions you can trust
Deep neural networks have become the gold-standard approach for the auto...
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04/18/2021
Non-asymptotic model selection in block-diagonal mixture of polynomial experts models
Model selection, via penalized likelihood type criteria, is a standard t...
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04/06/2021
A non-asymptotic penalization criterion for model selection in mixture of experts models
Mixture of experts (MoE) is a popular class of models in statistics and ...
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01/26/2021
Leveraging 3D Information in Unsupervised Brain MRI Segmentation
Automatic segmentation of brain abnormalities is challenging, as they va...
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12/09/2020
Rigid and Articulated Point Registration with Expectation Conditional Maximization
This paper addresses the issue of matching rigid and articulated shapes ...
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12/09/2020
Conjugate Mixture Models for Clustering Multimodal Data
The problem of multimodal clustering arises whenever the data are gather...
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05/14/2019
Approximate Bayesian computation via the energy statistic
Approximate Bayesian computation (ABC) has become an essential part of t...
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09/04/2015
EM Algorithms for Weighted-Data Clustering with Application to Audio-Visual Scene Analysis
Data clustering has received a lot of attention and numerous methods, al...
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09/30/2014
Hyper-Spectral Image Analysis with Partially-Latent Regression and Spatial Markov Dependencies
Hyper-spectral data can be analyzed to recover physical properties at la...
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08/10/2013
