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Construction of Bayesian Deformable Models via Stochastic Approximation
  Algorithm: A Convergence Study
v1v2 (latest)

Construction of Bayesian Deformable Models via Stochastic Approximation Algorithm: A Convergence Study

6 June 2007
S. Allassonnière
E. Kuhn
A. Trouvé
ArXiv (abs)PDFHTML

Papers citing "Construction of Bayesian Deformable Models via Stochastic Approximation Algorithm: A Convergence Study"

18 / 18 papers shown
DiTASK: Multi-Task Fine-Tuning with Diffeomorphic Transformations
DiTASK: Multi-Task Fine-Tuning with Diffeomorphic TransformationsComputer Vision and Pattern Recognition (CVPR), 2025
Krishna Sri Ipsit Mantri
Carola-Bibiane Schönlieb
Bruno Ribeiro
Chaim Baskin
Moshe Eliasof
591
6
0
09 Feb 2025
DiGRAF: Diffeomorphic Graph-Adaptive Activation Function
DiGRAF: Diffeomorphic Graph-Adaptive Activation Function
Krishna Sri Ipsit Mantri
Xinzhi Wang
Carola-Bibiane Schönlieb
Bruno Ribeiro
Beatrice Bevilacqua
Moshe Eliasof
GNN
339
3
0
02 Jul 2024
Why Target Networks Stabilise Temporal Difference Methods
Why Target Networks Stabilise Temporal Difference MethodsInternational Conference on Machine Learning (ICML), 2023
Matt Fellows
Matthew Smith
Shimon Whiteson
OODAAML
433
10
0
24 Feb 2023
Bayesian high-dimensional covariate selection in non-linear
  mixed-effects models using the SAEM algorithm
Bayesian high-dimensional covariate selection in non-linear mixed-effects models using the SAEM algorithmStatistics and computing (Stat. Comput.), 2022
Marion Naveau
Guillaume Kon Kam King
R. Rincent
Laure Sansonnet
Maud Delattre
438
6
0
02 Jun 2022
A Class of Two-Timescale Stochastic EM Algorithms for Nonconvex Latent
  Variable Models
A Class of Two-Timescale Stochastic EM Algorithms for Nonconvex Latent Variable Models
Belhal Karimi
Ping Li
BDL
204
0
0
18 Mar 2022
Bayesian Nonlinear Models for Repeated Measurement Data: An Overview,
  Implementation, and Applications
Bayesian Nonlinear Models for Repeated Measurement Data: An Overview, Implementation, and Applications
Se Yoon Lee
484
23
0
28 Jan 2022
Properties of the Stochastic Approximation EM Algorithm with Mini-batch
  Sampling
Properties of the Stochastic Approximation EM Algorithm with Mini-batch SamplingStatistics and computing (Stat. Comput.), 2019
Tabea Rebafka
E. Kuhn
C. Matias
215
25
0
22 Jul 2019
An Algorithm for Learning Shape and Appearance Models without
  Annotations
An Algorithm for Learning Shape and Appearance Models without Annotations
John Ashburner
Mikael Brudfors
Kevin Bronik
Yael Balbastre
MedImFedML
86
11
0
27 Jul 2018
Learning distributions of shape trajectories from longitudinal datasets:
  a hierarchical model on a manifold of diffeomorphisms
Learning distributions of shape trajectories from longitudinal datasets: a hierarchical model on a manifold of diffeomorphisms
Alexandre Bône
O. Colliot
S. Durrleman
243
41
0
27 Mar 2018
Statistical learning of spatiotemporal patterns from longitudinal
  manifold-valued networks
Statistical learning of spatiotemporal patterns from longitudinal manifold-valued networks
Igor Koval
Jean-Baptiste Schiratti
A. Routier
Michael Bacci
O. Colliot
S. Allassonnière
S. Durrleman
85
24
0
25 Sep 2017
Template estimation in computational anatomy: Fréchet means in top and
  quotient spaces are not consistent
Template estimation in computational anatomy: Fréchet means in top and quotient spaces are not consistent
L. Devilliers
S. Allassonnière
A. Trouvé
Xavier Pennec
194
7
0
12 Aug 2016
How to compute the barycenter of a weighted graph
How to compute the barycenter of a weighted graph
S. Gadat
Ioana Gavra
Laurent Risser
211
13
0
13 May 2016
Well-Posed Bayesian Geometric Inverse Problems Arising in Subsurface
  Flow
Well-Posed Bayesian Geometric Inverse Problems Arising in Subsurface Flow
M. Iglesias
Kui Lin
Andrew M. Stuart
336
88
0
22 Jan 2014
Bayesian methods in the Shape Invariant Model (I): Posterior contraction
  rates on probability measures
Bayesian methods in the Shape Invariant Model (I): Posterior contraction rates on probability measures
D. Bontemps
S. Gadat
295
0
0
08 Feb 2013
Bayesian posterior consistency in the functional randomly shifted curves
  model
Bayesian posterior consistency in the functional randomly shifted curves model
D. Bontemps
S. Gadat
255
0
0
21 Dec 2012
Convergent Stochastic Expectation Maximization algorithm with efficient
  sampling in high dimension. Application to deformable template model
  estimation
Convergent Stochastic Expectation Maximization algorithm with efficient sampling in high dimension. Application to deformable template model estimationComputational Statistics & Data Analysis (CSDA), 2012
S. Allassonnière
E. Kuhn
MedIm
406
22
0
25 Jul 2012
Random action of compact Lie groups and minimax estimation of a mean
  pattern
Random action of compact Lie groups and minimax estimation of a mean patternIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2011
Jérémie Bigot
Claire Christophe
S. Gadat
385
11
0
13 Oct 2011
Stochastic Algorithm For Parameter Estimation For Dense Deformable
  Template Mixture Model
Stochastic Algorithm For Parameter Estimation For Dense Deformable Template Mixture Model
S. Allassonnière
E. Kuhn
379
16
0
11 Feb 2008
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