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 ...

Quantum computing promises a new generation of computers capable of solving problems hundreds of millions of times more quickly than today’s fastest supercomputers. This is done by harnessing spooky ...

Machine learning models called convolutional neural networks (CNNs) power technologies like image recognition and language translation. A quantum counterpart—known as a quantum convolutional neural ...

A number of voices question when quantum computing technologies will deliver true business value, but IT and networking giant Cisco says that through new networking application demos for classical use ...

Researchers used the Q‑Chip to send quantum data over standard fiber using Internet Protocol (IP), showing that future quantum networks could run on today’s internet infrastructure. When you purchase ...

Quantum-inspired Leaky Integrate-and-Fire (QLIF) neurons for PyTorch, adaptive thresholds, dynamic spike probabilities, synaptic plasticity, neuromodulation, and optional qubit-based spike decisions.

Abstract: This work explores the integration of quantum computing within a classical Convolutional Neural Network (CNN) framework, leveraging a VGG16 model enhanced with a quantum Convolutional Neural ...

Over the past decade, deep learning (DL) techniques such as convolutional neural networks (CNNs) and long short-term memory (LSTM) networks have played a pivotal role in advancing the field of ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

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 ...