Variational autoencoders (VAEs) are deep latent space generative models that have been
immensely successful in multiple exciting applications in biomedical informatics such as …

Electronic Health Records (EHRs) are a valuable asset to facilitate clinical research and
point of care applications; however, many challenges such as data privacy concerns impede …

Groundwater modeling is an important tool for water resources management and aquifer
remediation. However, the inherent strong heterogeneity of the subsurface and scarcity of …

Variational Auto-Encoders (VAEs) are deep latent space generative models which have
been immensely successful in many applications such as image generation, image …

Co-speech gestures are a principal component in conveying messages and enhancing
interaction experiences between humans and critical ingredients in human-agent …

Data augmentation is a commonly used approach for addressing the issue of limited data
availability in machine learning. There are various methods available, including classical …

The pursuit of designing superconductors with high T c has been a long‐standing endeavor.
However, the widespread incorporation of doping in high T c superconductors significantly …

This paper introduces a bi-discriminator GAN for synthesizing tabular datasets containing
continuous, binary, and discrete columns. Our proposed approach employs an adapted …

Due to the high cost of labeling medical data such as electrocardiogram (ECG) signals, the
performance of classifiers suffers significantly from the lack of annotated data. In recent …

The spread of machine learning models, coupled with by the growing adoption of electronic
health records (EHRs), has opened the door for developing clinical decision support …