Abstract: Convolutional Neural Networks (CNNs) are extensively utilized for image classification due to their ability to exploit data correlations effectively. However, traditional CNNs encounter ...

The Heisenberg uncertainty principle puts a limit on how precisely we can measure certain properties of quantum objects. But researchers may have found a way to bypass this limitation using a quantum ...

Neuromorphic computing seeks to emulate the structural and functional organization of the brain, enabling computational systems to operate in ways that resemble biological neural processing. Its ...

For more than a century, scientists have wondered why physical structures like blood vessels, neurons, tree branches, and other biological networks look the way they do. The prevailing theory held ...

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...

gordicaleksa / pytorch-GAT My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an ...

Quarterly Form 13F filings allow investors to track which stocks Wall Street's billionaire investors have been buying and selling. Headwinds appear to be mounting for quantum computing pure-play ...

Abstract: Quantum Computing is a very promising paradigm given the ability that Quantum brings in terms of recognizing patterns which their classical counterparts very likely fail at.The intersection ...

Explore how neuromorphic chips and brain-inspired computing bring low-power, efficient intelligence to edge AI, robotics, and IoT through spiking neural networks and next-gen processors. Pixabay, ...

Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive technology and inclusive education. In an attempt to close that gap, I developed a ...