2 citations · 2 across the 3 of their papers we have counts for
3 papers
A Bayesian Non-parametric Approach to Generative Models: Integrating Variational Autoencoder and Generative Adversarial Networks using Wasserstein and Maximum Mean Discrepancy
Forough Fazeli-Asl, Michael Minyi Zhang
We propose a novel generative model within the Bayesian non-parametric learning (BNPL) framework to address some notable failure modes in generative adversarial networks (GANs) and…
A Semi-Bayesian Nonparametric Estimator of the Maximum Mean Discrepancy Measure: Applications in Goodness-of-Fit Testing and Generative Adversarial Networks
Forough Fazeli-Asl, Michael Minyi Zhang, Lizhen Lin
A classic inferential statistical problem is the goodness-of-fit (GOF) test. Such a test can be challenging when the hypothesized parametric model has an intractable likelihood and…
A Bayesian Nonparametric Estimation of Mutual Information
Luai Al-Labadi, Forough Fazeli-Asl, Zahra Saberi
Mutual information is a widely-used information theoretic measure to quantify the amount of association between variables. It is used extensively in many applications such as image…