Monte Carlo guided Diffusion for Bayesian linear inverse problems
De Sylvain Le Corff
Linear and nonlinear schemes for forward model reduction and inverse problems - Lecture 1
De Olga Mula Hernandez
Apparaît dans la collection : 2023 - T1B - WS2 - Networks of spiking neurons
Modern approaches for simulation-based inference build upon deep learning surrogates to enable approximate Bayesian inference with computer simulators. In this talk, we will review the main inference algorithms and discuss some applications specific to neuroscience.