MicroCloud Hologram Inc. Achieves Breakthrough in Practically Deployable Quantum Recurrent Neural Network (QRNN) Technology Oriented Toward Sequential Learning

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, released a core quantum machine learning technology oriented toward sequential learning tasks—the ...
Interesting Engineering on MSN

AI model predicts lithium battery life with up to 87 percent higher accuracy

Researchers have developed a hybrid AI model that significantly improves the accuracy of predicting ...
AZoRobotics

AI Model Achieves 99.24 % Accuracy in Breast Ultrasound Classification

This study presents a deep learning model for breast cancer detection, achieving 99.24% accuracy and improving clinical ...
Booth School of Business

Paper Deep Neural Networks for Estimation and Inference

We study deep neural networks and their use in semiparametric inference. We establish novel rates of convergence for deep feedforward neural nets. Our new rates are sufficiently fast (in some cases ...
EurekAlert!

Transfer learning-enhanced physics-informed neural network (TLE-PINN): A breakthrough in melt pool prediction for laser melting

The TLE-PINN method integrates EPINN and deep learning models through a transfer learning framework, combining strong physical constraints and efficient computational capabilities to accurately ...
Ars Technica

How a stubborn computer scientist accidentally launched the deep learning boom

During my first semester as a computer science graduate student at Princeton, I took COS 402: Artificial Intelligence. Toward the end of the semester, there was a lecture about neural networks. This ...
Scientific Research Publishing

A Spatio-Temporal Prediction Model for Wall Turbulence Based on Hybrid Neural Networks ()

The spatio-temporal evolution of wall-bounded turbulence is characterized by high nonlinearity, multi-scale dynamics, and ...