S. Allassonnière

发表

Towards a coherent statistical framework for dense deformable template estimation

Y. Amit, A. Trouvé, S. Allassonnière, 2007 .

Construction of Bayesian deformable models via a stochastic approximation algorithm: A convergence study

Estelle Kuhn, St'ephanie Allassonniere, Alain Trouv'e, 2007, 0706.0787.

Stochastic Algorithm For Parameter Estimation For Dense Deformable Template Mixture Model

S. Allassonnière, E. Kuhn, 2008, 0802.1521.

Learning the Clustering of Longitudinal Shape Data Sets into a Mixture of Independent or Branching Trajectories

Stanley Durrleman, Vianney Debavelaere, Stéphanie Allassonnière, 2020, International Journal of Computer Vision.

A New Class of EM Algorithms. Escaping Local Minima and Handling Intractable Sampling

S. Allassonnière, J. Chevallier, 2019 .

Medical image analysis methods in MR/CT-imaged acute-subacute ischemic stroke lesion: Segmentation, prediction and insights into dynamic evolution simulation models. A critical appraisal

S. Allassonnière, I. Rekik, J. Wardlaw, 2012, NeuroImage: Clinical.

Using longitudinal metamorphosis to examine ischemic stroke lesion dynamics on perfusion-weighted images and in relation to final outcome on T2-w images

S. Allassonnière, I. Rekik, J. Wardlaw, 2014, NeuroImage: Clinical.

Simulating Alzheimer's disease progression with personalised digital brain models

S. Allassonnière, S. Durrleman, B. Charlier, 2018 .

Spatiotemporal Propagation of the Cortical Atrophy: Population and Individual Patterns

S. Allassonnière, Jean-Baptiste Schiratti, S. Durrleman, 2018, Front. Neurol..

Mixed-effects model for the spatiotemporal analysis of longitudinal manifold-valued data

Stanley Durrleman, Olivier Colliot, Stéphanie Allassonnière, 2015 .

MAP Estimation of Statistical Deformable Template Via Nonlinear Mixed Effect Models : Deterministic and Stochastic Approaches

Alain Trouvé, Stéphanie Allassonnière, Estelle Kuhn, 2008 .

BAYESIAN DEFORMABLE MODELS BUILDING 3 a penalized likelihood ( PL ) or the more recent maximum description length approach in

S. Allassonnière, E. Kuhn, Alain, 2009 .

Deterministic Approximate EM Algorithm; Application to the Riemann Approximation EM and the Tempered EM

S. Allassonnière, S. Durrleman, Thomas Lartigue, 2020, Algorithms.

Edinburgh Explorer Using longitudinal metamorphosis to examine ischemic stroke lesion dynamics on perfusion-weighted and relation to final outcome on T2-w images

S. Allassonnière, I. Rekik, T. Carpenter, 2014 .

Phase-based metamorphosis of diffusion lesion in relation to perfusion values in acute ischemic stroke

M. Luby, S. Allassonnière, I. Rekik, 2015, NeuroImage: Clinical.

Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder

S. Allassonnière, Ninon Burgos, E. Thibeau-Sutre, 2021, IEEE transactions on pattern analysis and machine intelligence.

Pythae: Unifying Generative Autoencoders in Python -- A Benchmarking Use Case

S. Allassonnière, Cl'ement Chadebec, Louis J. Vincent, 2022, 2206.08309.

Deciphering the progression of PET alterations using surface-based spatiotemporal modeling

S. Allassonnière, S. Durrleman, O. Colliot, 2019 .

Medical image analysis methods in MR/CT-imaged acute-subacute ischemic stroke lesion

S. Allassonnière, I. Rekik, J. Wardlaw, 2018 .

Pythae: Unifying Generative Autoencoders in Python - A Benchmarking Use Case

S. Allassonnière, Cl'ement Chadebec, Louis J. Vincent, 2022, ArXiv.

A Geometric Perspective on Variational Autoencoders

S. Allassonnière, Cl'ement Chadebec, 2022, 2209.07370.

Asymptotic analysis of a matrix latent decomposition model

S. Allassonnière, S. Durrleman, Clément Mantoux, 2022, ESAIM: Probability and Statistics.

A Geometric Perspective on Variational Autoencoders

S. Allassonnière, Clément Chadebec, 2022, NeurIPS.

Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder

S. Allassonnière, Ninon Burgos, E. Thibeau-Sutre, 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence.

A Model-Based Reinforcement Learning Approach for a Rare Disease Diagnostic Task pdf

Stéphanie Allassonnière, Erwan Le Pennec, Antoine Neuraz, 2018, ArXiv.

Learning spatiotemporal trajectories from manifold-valued longitudinal data

Stanley Durrleman, Olivier Colliot, Stéphanie Allassonnière, 2015, NIPS.

Probabilistic atlas and geometric variability estimation to drive tissue segmentation

Bertrand Thirion, Stéphanie Allassonnière, Hao Xu, 2014, Statistics in medicine.

Bayesian Estimation of Probabilistic Atlas for Anatomically-Informed Functional MRI Group Analyses

Hao Xu, Bertrand Thirion, Stéphanie Allassonnière, 2013, MICCAI.

AD Course Map charts Alzheimer’s disease progression

S. Allassonnière, S. Durrleman, B. Charlier, 2021, Scientific Reports.

Sparse Adaptive Parameterization of Variability in Image Ensembles

Stanley Durrleman, Sarang C. Joshi, Stéphanie Allassonnière, 2012, International Journal of Computer Vision.

Convergent stochastic Expectation Maximization algorithm with efficient sampling in high dimension. Application to deformable template model estimation

Stéphanie Allassonnière, Estelle Kuhn, S. Allassonnière, 2012, Comput. Stat. Data Anal..

A new class of stochastic EM algorithms. Escaping local maxima and handling intractable sampling

Stéphanie Allassonnière, Juliette Chevallier, S. Allassonnière, 2021, Comput. Stat. Data Anal..

New Results - Deformable Template estimation for joint anatomical and functional brain images

Hao Xu, Bertrand Thirion, Stéphanie Allassonnière, 2013 .

Description and clinical validation of a real-time AI diagnostic companion for fetal ultrasound examination

S. Allassonnière, R. Besson, T. Attié-Bitach, 2021, medRxiv.

A Bayesian Mixed-Effects Model to Learn Trajectories of Changes from Repeated Manifold-Valued Observations

Stanley Durrleman, Olivier Colliot, Stéphanie Allassonnière, 2017, J. Mach. Learn. Res..

Understanding the Variability in Graph Data Sets through Statistical Modeling on the Stiefel Manifold

Stanley Durrleman, Stéphanie Allassonnière, Stéphane Epelbaum, 2021, Entropy.

Inconsistency of Template Estimation by Minimizing of the Variance/Pre-Variance in the Quotient Space

Alain Trouvé, Xavier Pennec, Stéphanie Allassonnière, 2017, Entropy.

Identification of glucocorticoid-related molecular signature by whole blood methylome analysis

S. Allassonnière, F. Beuschlein, J. Bertherat, 2021, European journal of endocrinology.

A Mixed-Effects Model with Time Reparametrization for Longitudinal Univariate Manifold-Valued Data

Stanley Durrleman, Olivier Colliot, Stéphanie Allassonnière, 2015, IPMI.

Spatiotemporal Dynamic Simulation of Acute Perfusion/Diffusion Ischemic Stroke Lesions Evolution: A Pilot Study Derived from Longitudinal MR Patient Data

Joanna M. Wardlaw, Stanley Durrleman, Islem Rekik, 2013, Comput. Math. Methods Medicine.

Learning spatiotemporal piecewise-geodesic trajectories from longitudinal manifold-valued data

Stéphanie Allassonnière, Juliette Chevallier, Stephane Oudard, 2017, NIPS.

Simulation of virtual cohorts increases predictive accuracy of cognitive decline in MCI subjects pdf

Stanley Durrleman, Stéphanie Allassonnière, Igor Koval, 2019, ArXiv.

On the convergence of stochastic approximations under a subgeometric ergodic Markov dynamic

Stanley Durrleman, Vianney Debavelaere, Stéphanie Allassonnière, 2021, Electronic Journal of Statistics.

Proof of the convergence of Stochastic Approximations under a subgeometric ergodic Markov dynamic

S. Allassonnière, S. Durrleman, Vianney Debavelaere, 2020 .

Statistical Learning of Spatiotemporal Patterns from Longitudinal Manifold-Valued Networks pdf

Stanley Durrleman, Olivier Colliot, Stéphanie Allassonnière, 2017, MICCAI.

Data Augmentation with Variational Autoencoders and Manifold Sampling

Stéphanie Allassonnière, Clément Chadebec, S. Allassonnière, 2021, DGM4MICCAI/DALI@MICCAI.

Data Generation in Low Sample Size Setting Using Manifold Sampling and a Geometry-Aware VAE

S. Allassonnière, Clément Chadebec, 2021, ArXiv.

Spatio-temporal mixture process estimation to detect dynamical changes in population

S. Allassonnière, A. Jannot, S. Pruilh, 2022, Artificial Intelligence in Medicine.

Gaussian Graphical Model Exploration and Selection in High Dimension Low Sample Size Setting

Stanley Durrleman, Olivier Colliot, Simona Bottani, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Special Issue: Stochastic Algorithms and Their Applications

S. Allassonnière, 2022, Algorithms.

Pythae: Unifying Generative Autoencoders in Python - A Benchmarking Use Case

S. Allassonnière, Louis J. Vincent, Clément Chadebec, 2022, NeurIPS.

Improving Multimodal Joint Variational Autoencoders through Normalizing Flows and Correlation Analysis

S. Allassonnière, Clément Chadebec, Agathe Senellart, 2023, ArXiv.

Variational Inference for Longitudinal Data Using Normalizing Flows

S. Allassonnière, Clément Chadebec, 2023, ArXiv.

Learning the Clustering of Longitudinal Shape Data Sets into a Mixture of Independent or Branching Trajectories

S. Allassonnière, S. Durrleman, Vianney Debavelaere, 2020, International Journal of Computer Vision.

Clustering of Longitudinal Shape Data Sets Using Mixture of Separate or Branching Trajectories

Stanley Durrleman, Alexandre Bône, Vianney Debavelaere, 2019, MICCAI.

Aircraft classification with a low resolution infrared sensor

É. Moulines, S. Allassonnière, S. Lefebvre, 2011, 2011 IEEE Statistical Signal Processing Workshop (SSP).

Detection and classification of poorly known aircraft with a low-resolution infrared sensor

Eric Moulines, Stéphanie Allassonnière, Sidonie Lefebvre, 2011, Defense + Commercial Sensing.

Tumor growth parameters estimation and source localization from a unique time point: Application to low-grade gliomas

Hervé Delingette, Olivier Clatz, Nicholas Ayache, 2013, Comput. Vis. Image Underst..

Robust Reinforcement Learning with Distributional Risk-averse formulation

S. Allassonnière, E. L. Pennec, Pierre Clavier, 2022, ArXiv.

Detecting Long Distance Conditional Correlations Between Anatomical Regions Using Gaussian Graphical Models

Christophe Giraud, Pierre Jolivet, Stéphanie Allassonnière, 2011 .

Bayesian Mixed Effect Atlas Estimation with a Diffeomorphic Deformation Model

Stanley Durrleman, Stéphanie Allassonnière, Estelle Kuhn, 2015, SIAM J. Imaging Sci..

Stochastic algorithm for Bayesian mixture effect template estimation

S. Allassonnière, E. Kuhn, 2010 .

Bayesian Deformable Models Building via Stochastic Approximation Algorithm: A Convergence Study

Alain Trouvé, Stéphanie Allassonnière, Estelle Kuhn, 2007 .

Geodesic Shooting and Diffeomorphic Matching Via Textured Meshes

Alain Trouvé, Laurent Younes, Stéphanie Allassonnière, 2005, EMMCVPR.

Template Estimation in Computational Anatomy: Fréchet Means Top and Quotient Spaces Are Not Consistent

Alain Trouvé, Xavier Pennec, Stéphanie Allassonnière, 2016, SIAM J. Imaging Sci..

On the curved exponential family in the Stochastic Approximation Expectation Maximization Algorithm

Vianney Debavelaere, Stéphanie Allassonnière, S. Allassonnière, 2021, ESAIM: Probability and Statistics.

Statistical models for deformable templates in image and shape analysis

Stéphanie Allassonnière, Jérémie Bigot, Florian Maire, 2013 .

Geometry-Aware Hamiltonian Variational Auto-Encoder pdf

Cl'ement Chadebec, Cl'ement Mantoux, St'ephanie Allassonniere, 2020, ArXiv.