The THz- and Millimeterwave Techniques group is in search of a doctoral researcher for an interdisciplinary THz medical imaging research program developing diffractive optical elements (DOEs) and ...

AI became powerful because of interacting mechanisms: neural networks, backpropagation and reinforcement learning, attention, ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...

Enterprise data systems now sit beside ranking, inference and decision pipelines that influence what users see, interact with, and act on. At scale, these systems often remain operational while ...

Abstract: Federated learning (FL), a distributed learning paradigm focused on preserving data privacy, faces challenges due to varying data distributions among clients, impacting global model ...

ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...

African fintech giant Chipper Cash announces over half of its Bitcoin transactions now run on the Lightning Network via Voltage, driving faster, cheaper, and more reliable payments across the ...

Abstract: This work investigates the generalization behavior of deep neural networks (DNNs), focusing on the phenomenon of “fooling examples,” where DNNs confidently classify inputs that appear random ...

ABSTRACT: Cybersecurity has emerged as a global concern, amplified by the rapid expansion of IoT devices and the growing digitization of systems. In this context, traditional security solutions such ...