AI makes quantum field theories computable

How can quantum field theories be best formulated on a lattice to optimally simulate them on a computer? The answer comes ...
New Scientist

Quantum neural network may be able to cheat the uncertainty principle

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 ...
Frontiers

Bridging neuromorphic computing and deep learning for next-generation neural data interpretation

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 ...
Science Daily

Quantum structured light could transform secure communication and computing

Scientists are learning to engineer light in rich, multidimensional ways that dramatically increase how much information a single photon can carry. This leap could make quantum communication more ...
Hosted on MSN

Neural network Python from scratch with softmax

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 ...
Phys.org

Metal–metal bonded molecule achieves stable spin qubit state, opening path toward quantum computing materials

Researchers at Kumamoto University, in collaboration with colleagues in South Korea and Taiwan, have discovered that a unique cobalt-based molecule with metal–metal bonds can function as a spin ...
GitHub

My Graph Neural Network Stack

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 ...
IEEE

QcNet: A Hybrid Quantum-Classical Neural Network for Multi-Class Image Classification

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 ...
techtimes

Neuromorphic Chips and 'Brain‑Like' Computing: How Next‑Gen Chips May Change Phones, Robots, and IoT Devices

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, ...
TMCnet

Bridging Silence: A Real-Time Sign Language to English Text Translation System Using Python, OpenCV, and Convolutional Neural Networks

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 ...
IEEE

Compressing Neural Networks on Limited Computing Resources

Abstract: Network compression is a crucial technique for applying deep learning models to edge or mobile devices. However, the cost of achieving higher benchmark performance through compression is ...