Folded Hamiltonian Monte Carlo for Bayesian Generative Adversarial Networks

no code implementations • 29 Sep 2021 • Narges Pourshahrokhi, Samaneh Kouchaki, Yunpeng Li, Payam M. Barnaghi

Generative Adversarial Networks (GANs) can learn complex distributions over images, audio, and data that are difficult to model.

A Hamiltonian Monte Carlo Model for Imputation and Augmentation of Healthcare Data

1 code implementation • 3 Mar 2021 • Narges Pourshahrokhi, Samaneh Kouchaki, Kord M. Kober, Christine Miaskowski, Payam Barnaghi

A Bayesian approach to impute missing values and creating augmented samples in high dimensional healthcare data is proposed in this work.

Bayesian Inference Imputation