4 papers
Convergence of projected stochastic natural gradient variational inference for various step size and sample or batch size schedules
Thomas Guilmeau, Hadrien Hendrikx, Florence Forbes
Stochastic natural gradient variational inference (NGVI) is a popular and efficient algorithm for Bayesian inference. Despite empirical success, the convergence of this method is s…
Active MRI Acquisition with Diffusion Guided Bayesian Experimental Design
Jacopo Iollo, Geoffroy Oudoumanessah, Carole Lartizien +2
A key challenge in maximizing the benefits of Magnetic Resonance Imaging (MRI) in clinical settings is to accelerate acquisition times without significantly degrading image quality…
Bayesian Experimental Design via Contrastive Diffusions
Jacopo Iollo, Christophe Heinkelé, Pierre Alliez +1
Bayesian Optimal Experimental Design (BOED) is a powerful tool to reduce the cost of running a sequence of experiments. When based on the Expected Information Gain (EIG), design op…
PASOA- PArticle baSed Bayesian Optimal Adaptive design
Jacopo Iollo, Christophe Heinkelé, Pierre Alliez +1
We propose a new procedure named PASOA, for Bayesian experimental design, that performs sequential design optimization by simultaneously providing accurate estimates of successive…