New Scientist

Quantum neural network may be able to cheat the uncertainty principle

Calculations show that injecting randomness into a quantum neural network could help it determine properties of quantum ...
GitHub

Interpretable Bayesian Tensor Network Kernel Machines with Automatic Rank and Feature Selection

This repository contains the source code used to produce the results obtained in Interpretable Bayesian Tensor Network Kernel Machines with Automatic Rank and Feature Selection submitted to Journal of ...
Semiconductor Engineering

Accelerating Semiconductor Innovation Through Machine Learning-Driven Modeling

The semiconductor industry is entering an era of unprecedented complexity, driven by advanced architectures such as Gate-All-Around (GAA) transistors, wide-bandgap materials like GaN and SiC, and ...
IEEE

Deep Neural Networks Internal Representation via Neuron Community Exploration

Abstract: Deep neural networks have demonstrated exceptional performance in extracting task-specific representations from datasets, earning widespread recognition and application. However, the ...
Beebom

What is the Difference Between Deep Learning and Machine Learning

Machine learning requires humans to manually label features while deep learning automatically learns features directly from raw data. ML uses traditional algorithms like decision tress, SVM, etc., ...
IEEE

Machine Learning in Intelligent Networks: Architectures, Techniques, and Use Cases

Abstract: Integrating machine learning (ML) into intelligent networks (INs) has redefined the capabilities of modern communication systems by enabling real-time decision-making, adaptive optimization, ...