Bayesian Inference with Generative Adversarial Network Priors. - Dhruv Patel 001; Assad A. Oberai (CoRR, 2019)

GAN-based Priors for Quantifying Uncertainty. - Dhruv V. Patel; Assad A. Oberai (CoRR, 2020)

Solution of Physics-based Bayesian Inverse Problems with Deep Generative Priors. - Dhruv V. Patel; Deep Ray; Assad A. Oberai (CoRR, 2021)

GAN-Based Priors for Quantifying Uncertainty in Supervised Learning. - Dhruv V. Patel; Assad A. Oberai (SIAM/ASA J. Uncertain. Quantification, 2021)

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 (CoRR, 2022)

Variationally Mimetic Operator Networks. - Dhruv Patel 001; Deep Ray; Michael R. A. Abdelmalik; Thomas J. R. Hughes; Assad A. Oberai (CoRR, 2022)

Probabilistic medical image imputation via deep adversarial learning. - Ragheb Raad; Dhruv Patel 001; Chiao-Chih Hsu; Vijay Kothapalli; Deep Ray; Bino A. Varghese; Darryl Hwang; Inderbir S. Gill; Vinay A. Duddalwar; Assad A. Oberai (Eng. Comput., 2022)

A dimension-reduced variational approach for solving physics-based inverse problems using generative adversarial network priors and normalizing flows. - Agnimitra Dasgupta; Dhruv V. Patel; Deep Ray; Erik A. Johnson; Assad A. Oberai (CoRR, 2023)

Multi-fidelity Hamiltonian Monte Carlo. - Dhruv V. Patel; Jonghyun Lee 005; Matthew W. Farthing; Peter K. Kitanidis; Eric F. Darve (CoRR, 2024)