Deep neural networks with millions of parameters are at the heart of many state of the art computer vision models. However, recent works have shown that models with much smaller number of parameters can often perform just ...

Physics-Informed Neural Networks (PINNs) and its variants have emerged as a tool for solving differential equations in the past few years. Although several variants of PINNs have been proposed, the majority of these ...

Lesion segmentation and their progression prediction in medical imaging relies critically on the availability of manually annotated, heterogeneous large pathological datasets. Acquiring such diverse large datasets is also ...

Traditional strategies to build machine learning based classification systems employ discrete labels as targets. This limits the usefulness of such systems in two ways. First, the generalizability of these systems is limited ...

Though deep learning has achieved significant successes in many computer vision tasks, the state-of-the-art approaches rely on the availability of a large amount of labeled data for supervision, collection of which is ...

Computed Tomography (CT) Perfusion imaging is a non-invasive medical imaging modality that has also established itself as a fast and economical imaging modality for diagnosing cerebrovascular diseases such as acute ischemia, ...

Convergence of iterative algorithms in solving large linear systems is largely affected by the condition number of the matrix. Preconditioners reduce the condition number of the system matrix, thereby letting the linear ...

With a goal toward a net-zero energy supply, hydrogen, hydrogen-enriched natural gas, and biofuels, which reduce the carbon footprint, are actively being considered for firing stationary gas turbine engines. In this regard, ...

In this era of Big Data Analytics, much of the semi-structured data has inherent interconnectivity between representative entities. These are increasingly being modeled as property graphs because of the semantic advantages ...

Graphs with temporal characteristics are increasingly becoming prominent. Their vertices, edges and attributes are annotated with a lifespan, allowing one to add or remove vertices and edges. Such graphs can grow to millions ...