Networking specialist HighPoint has launched its Rocket 7638D PCIe 5.0 switch card designed to enable direct interconnection between an Nvidia AI GPUs and NVMe storage devices, which could greatly ...

Abstract: To build Neural Networks (NNs) on edge devices, Binarized Neural Network (BNN) has been proposed on the software side, while Computing-in-Memory (CiM) architecture has been proposed on the ...

This project contains implementations of simple neural network models, including training scripts for PyTorch and Lightning frameworks. The goal is to provide a modular, easy-to-understand codebase ...

This repository demonstrates a complete workflow for training and deploying neural networks directly inside MetaTrader 5. The goal is to show that the MQL5 language can handle custom machine learning ...

Abstract: An analysis was made of physics-informed neural networks used to solve partial differential equations. The prospects for the implementation of physics-informed neural networks in the MATLAB ...

The researchers stress that this scale of work was made possible by a coordinated ecosystem of computational services: CyVerse for data storage, OSG OS Pool for high-throughput computing, Pegasus for ...

Despite the widespread success of neural networks, their susceptibility to adversarial examples remains a significant challenge. Adversarial training (AT) has emerged as an effective approach to ...

Spiking neural networks (SNNs), which are the next generation of artificial neural networks (ANNs), offer a closer mimicry to natural neural networks and hold promise for significant improvements in ...

1 College of Physics and Optoelectronic Engineering, Ocean University of China, Qingdao, China 2 College of Marine Technology, Ocean University of China, Qingdao, China The study of the low-frequency ...

Graph Neural Networks GNNs have become a powerful tool for analyzing graph-structured data, with applications ranging from social networks and recommendation systems to bioinformatics and drug ...