Closed-form relations for limiting eigenvalues of an infinite k-periodic spatial lattice in any number of dimensions d, and its semi-analytical extensions for any given size n of the lattice with free-free boundary ...

Artificial Neural Networks (ANN) have been very successful due to their ability to extract meaningful information without any need for pre-processing raw data. First artificial neural networks were created in essence to ...

Many high performance computing applications in computational fluid dynamics, electromagnetics etc. need to solve a linear system of equations $Ax=b$. For linear systems where $A$ is generally large and sparse, Krylov ...

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 ...

Analyzing humans and their activities takes a central role in computer vision. This requires machine learning models to encapsulate both the diverse poses and appearances exhibited by humans. Estimating the 3D poses of ...

Deep learning models have shown impressive performance across a wide spectrum of computer vision applications, including medical diagnosis and autonomous driving. One of the major concerns that these models face is their ...

Obtaining high performance and scalability for high performance applications are challenging. There are various bottlenecks including, higher rate of memory access, complex algorithm, high rate of communication, big ...

The benefits of autonomous mobile platforms, such as Unmanned Aerial Vehicles (UAVs) equipped with onboard cameras, are enhanced by compact edge accelerators that are co-located, such as the NVIDIA Jetson with 100s of CUDA ...

The human reference genome serves as a foundational baseline for comparing newly sequenced human genomes. With the growing availability of high-quality human genome assemblies, there is now an opportunity to modernize the ...