Collection 2019 - T1 - WS2 - Statistical Modeling for Shapes and Imaging
Apparaît dans la collection : 2019 - T1 - The Mathematics of Imaging
Date(s) 11/03/2019 - 15/03/2019
Mathématiques
et Interactions
Date(s) 11/03/2019 - 15/03/2019
-
Toutes les vidéos de la collection (25)
![Synthesizing stochastic microstructures for additive manufacturing]()
48:51publiée le 16 avril 2019Synthesizing stochastic microstructures for additive manufacturing
De Sylvain Lefèbvre
![Detecting Overfitting of Deep Generative Networks via Latent Recovery]()
38:40publiée le 16 avril 2019Detecting Overfitting of Deep Generative Networks via Latent Recovery
De Julien Rabin
![3D Point Cloud Classification, Segmentation and Normal estimation, using 3D Modified Fisher Vector Representation and Convolutional Neural Networks]()
46:27publiée le 16 avril 20193D Point Cloud Classification, Segmentation and Normal estimation, using 3D Modified Fisher Vector Representation and Convolutional Neural Networks
De Michael Lindenbaum
![Total variation denoising with iterated conditional expectation]()
42:55publiée le 16 avril 2019Total variation denoising with iterated conditional expectation
De Cécile Louchet
![Hybrid sparse stochastic processes and the resolution of linear inverse problems]()
50:44publiée le 16 avril 2019Hybrid sparse stochastic processes and the resolution of linear inverse problems
De Michael Unser
![Lipschitz-Killing curvatures of excursion sets for 2D random fields]()
41:28publiée le 16 avril 2019Lipschitz-Killing curvatures of excursion sets for 2D random fields
De Hermine Biermé
![Efficient sampling through variable splitting-inspired bayesian hierarchical models]()
45:08publiée le 16 avril 2019Efficient sampling through variable splitting-inspired bayesian hierarchical models
De Pierre Chainais
![Statistical aspects of stochastic algorithms for entropic optimal transportation between probability measures]()
43:32publiée le 16 avril 2019Statistical aspects of stochastic algorithms for entropic optimal transportation between probability measures
De Jérémie Bigot
![Stochastic Approximation-based algorithms, when the Monte Carlo bias does not vanish]()
40:46publiée le 16 avril 2019Stochastic Approximation-based algorithms, when the Monte Carlo bias does not vanish
De Gersende Fort
![Mixed-effect model for the spatiotemporal analysis of longitudinal manifold-valued data]()
41:00publiée le 16 avril 2019Mixed-effect model for the spatiotemporal analysis of longitudinal manifold-valued data
De Stéphanie Allassonnière
![A fast statistical colocalization method for 3D live cell imaging and super-resolution microscopy]()
42:17publiée le 16 avril 2019A fast statistical colocalization method for 3D live cell imaging and super-resolution microscopy
De Charles Kervrann
![Multiple objects detection in biological images using a Marked Point Process Framework]()
50:47publiée le 16 avril 2019Multiple objects detection in biological images using a Marked Point Process Framework
De Xavier Descombes
![Création des mondes virtuels : Objets auto-similaires et distributions d'éléments]()
01:05:57publiée le 16 avril 2019Création des mondes virtuels : Objets auto-similaires et distributions d'éléments
De Marie-Paule Cani
![From currents to oriented varifolds for data fidelity metrics; growth models for computational anatomy]()
49:32publiée le 16 avril 2019From currents to oriented varifolds for data fidelity metrics; growth models for computational anatomy
De Irène Kaltenmark
![Kernel norms on normal cycles and the KeOps library for linear memory reductions over datasets]()
49:04publiée le 16 avril 2019Kernel norms on normal cycles and the KeOps library for linear memory reductions over datasets
De Joan Glaunès
![Bayesian inference and convex geometry: theory, methods, and algorithms]()
49:33publiée le 16 avril 2019Bayesian inference and convex geometry: theory, methods, and algorithms
De Marcelo Pereyra
![Modular large deformation and shape aware metrics in shape analysis: How to make things simple (and meaningful)?]()
55:38publiée le 16 avril 2019Modular large deformation and shape aware metrics in shape analysis: How to make things simple (and meaningful)?
De Alain Trouvé
