Solving Bayesian Inverse Problems via Variational Autoencoders

5 December 2019

Papers citing "Solving Bayesian Inverse Problems via Variational Autoencoders"

9 / 9 papers shown

Title
Good Things Come in Pairs: Paired Autoencoders for Inverse Problems Matthias Chung Bas Peters Michael Solomon 34 0 0 10 May 2025
Bayesian Inverse Problems Meet Flow Matching: Efficient and Flexible Inference via Transformers Daniil Sherki Ivan V. Oseledets Ekaterina A. Muravleva 62 0 0 03 Mar 2025
A Primer on Variational Inference for Physics-Informed Deep Generative Modelling Alex Glyn-Davies A. Vadeboncoeur O. Deniz Akyildiz Ieva Kazlauskaite Mark Girolami PINN 70 0 0 10 Sep 2024
Bi-level Guided Diffusion Models for Zero-Shot Medical Imaging Inverse Problems Hossein Askari Fred Roosta Hongfu Sun MedIm DiffM 38 3 0 04 Apr 2024
An autoencoder compression approach for accelerating large-scale inverse problems J. Wittmer Jacob Badger H. Sundar T. Bui-Thanh AI4CE 29 1 0 10 Apr 2023
Quantifying uncertainty for deep learning based forecasting and flow-reconstruction using neural architecture search ensembles R. Maulik Romain Egele Krishnan Raghavan Prasanna Balaprakash UQCV AI4TS AI4CE 22 6 0 20 Feb 2023
Randomized Maximum Likelihood via High-Dimensional Bayesian Optimization Valentin Breaz Richard D. Wilkinson 19 0 0 17 Apr 2022
The efficacy and generalizability of conditional GANs for posterior inference in physics-based inverse problems Deep Ray Harisankar Ramaswamy Dhruv V. Patel Assad A. Oberai CML AI4CE 13 21 0 15 Feb 2022
Solution of Physics-based Bayesian Inverse Problems with Deep Generative Priors Dhruv V. Patel Deep Ray Assad A. Oberai AI4CE 16 37 0 06 Jul 2021