University of Delaware

Star power

The neural network approach uses multiple or “deep” layers that learn to identify increasingly complex features in data. The ...
Analytics Insight

Best Deep Learning Books to Read in 2026

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...

AI sheds light on hard-to-study ocean currents

The Indonesian Throughflow carries both warm water and fresh water from the Pacific into the Indian Ocean. As the only ...
Hosted on MSN

Network in Network (NiN) Explained – Deep Neural Network Tutorial with PyTorch

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...
Hosted on MSN

Backpropagation from Scratch in Python – Step by Step Neural Network Tutorial

Learn how backpropagation works by building it from scratch in Python! This tutorial explains the math, logic, and coding behind training a neural network, helping you truly understand how deep ...
C&EN

A Multi-Stage Graph Neural Network–Physics-Informed Neural Network (GNN–PINN) Framework for Thermodynamic Property Prediction

Department of Chemistry and Chemical Engineering, Education and Research Center for Smart Energy and Materials, Inha University, Incheon 22212, Republic of Korea ...
Frontiers

Convolutional neural networks decode finger movements in motor sequence learning from MEG data

1 Institute of Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia 2 Department of Learning, Data Analytics and Technology, Section Cognition, Data and ...
pv magazine International

PV module fault diagnosis uses convolutional neural network

Researchers in China have created a dataset of various PV faults and normalized it to accommodate different array sizes and typologies. After testing the new approach in combination with the 1D-CNN ...
IEEE

A Tutorial on Quantum Convolutional Neural Networks (QCNN)

Abstract: Convolutional Neural Network (CNN) is a popular model in computer vision and has the advantage of making good use of the correlation information of data. However, CNN is challenging to learn ...