Hybrid Quantum: Classical Architectures For Machine Learning

As you begin your hybrid quantum approach, here are the advantages, use cases and limitations to keep in mind.
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 ...
Frontiers

CatBoost-Enhanced Convolutional Neural Network Framework with Explainable Artificial Intelligence for Smart-Grid Stability Forecasting

The final, formatted version of the article will be published soon. Mobile robots, such as drones, rovers, and autonomous ground units, are becoming more crucial for inspecting, monitoring, and ...
GEN

AI Detects Schizophrenia and Bipolar Disorder Neural Signatures in Organoids

Neurological disorders, such as schizophrenia and bipolar disorder, remain challenging to diagnose due to the absence of objective biomarkers. Current assessments largely rely on subjective clinical ...
C&EN

Ferroelectric/Antiferroelectric HfZrO x Artificial Synapses/Neurons for Convolutional Neural Network–Spiking Neural Network Neuromorphic Computing

College of Integrated Circuits and Micro-Nano Electronics, School of Microelectronics, State Key Laboratory of Integrated Chip and System, Fudan University, Shanghai 200433, China ...
Hosted on MSN

Max Pooling in Convolutional Neural Network

In this video, we will understand what is Max Pooling in Convolutional Neural Network and why do we use it. Max Pooling in Convolutional Neural Network is an important part of the CNN Architecture, ...
GitHub

Incorrect output-shape description in 01_neural_networks tutorial

"For the EstimatorQNN, the expected output shape for the forward pass is (1, num_qubits * num_observables)” In practice, the forward pass returns an array of shape (batch_size, num_observables)—one ...
C&EN

From Neural Networks to Transformers: Achieving High and Fast Precision in Fluorescence Correlation Spectroscopy Analysis

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. To address the challenges in FCS data fitting, we propose a ...
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 ...
Frontiers

Association prediction of lncRNAs and diseases using multiview graph convolution neural network

1 College of Computer Science and Engineering, Changsha University, Changsha, Hunan, China 2 Department of Information and Computing Science, College of Mathematics, Changsha University, Changsha, ...