Use of generative models and deep learning for physics-based systems is
...
Variational inference is an increasingly popular method in statistics an...
Electronic health records (EHR) often contain sensitive medical informat...
We propose a data-driven framework to increase the computational efficie...
We analyze the regression accuracy of convolutional neural networks asse...
Approximating probability distributions can be a challenging task,
parti...
Novel Magnetic Resonance (MR) imaging modalities can quantify hemodynami...
Fast inference of numerical model parameters from data is an important
p...
Computational models are increasingly used for diagnosis and treatment o...
Standard approaches for uncertainty quantification (UQ) in cardiovascula...