The rapid advances in the internet and communication fields have resulted in a huge
increase in the network size and the corresponding data. As a result, many novel attacks are …

Physics-informed neural networks (PINNs) encode physical conservation laws and prior
physical knowledge into the neural networks, ensuring the correct physics is represented …

Mutational signature analysis is commonly performed in cancer genomic studies. Here, we
present SigProfilerExtractor, an automated tool for de novo extraction of mutational …

In computer architecture, significant innovation frequently comes from industry. However, the
simulation tools used by industry are often not released for open use, and even when they …

A datacentre stores information and manages data access in fast and reliable manner.
Failure of datacentre operation is not an option and can be catastrophic. Internet of things …

Summary Flying Ad Hoc Network (FANET) has obtained a great deal of interest over recent
times because of their significant applications. Thus, various examinations have been led on …

Deep neural networks have become the compelling solution for the applications such as
image classification, object detection, speech recognition, and machine translation …

The dynamics of computer networks have changed rapidly over the past few years due to a
tremendous increase in the volume of the connected devices and the corresponding …

Leveraging sparsity in deep neural network (DNN) models is promising for accelerating
model inference. Yet existing GPUs can only leverage the sparsity from weights but not …

We present a method for transparently identifying ineffectual computations during inference
with Deep Learning models. Specifically, by decomposing multiplications down to the bit …