Solving inverse problems in stochastic models using deep neural networks and adversarial training

Circumventing the solution of inverse problems in mechanics through deep learning: Application to elasticity imaging

(2019) Dhruv Patel et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Adversarial uncertainty quantification in physics-informed neural networks

(2019) Yibo Yang et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Fusion-based foreground enhancement for background subtraction using multivariate multi-model Gaussian distribution

(2018) Thangarajah Akilan et al.   INFORMATION SCIENCES

Lp-WGAN: Using Lp-norm normalization to stabilize Wasserstein generative adversarial networks

(2018) Changsheng Zhou et al.   KNOWLEDGE-BASED SYSTEMS

A Tutorial on Fisher information

(2017) Alexander Ly et al.   JOURNAL OF MATHEMATICAL PSYCHOLOGY

Variational Inference: A Review for Statisticians

(2017) David M. Blei et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

Data-driven discovery of partial differential equations

(2017) Samuel H. Rudy et al.   Science Advances

On the empirical estimation of integral probability metrics

(2012) Bharath K. Sriperumbudur et al.   Electronic Journal of Statistics