Scientific American

Could Symbolic AI Unlock Human-like Intelligence?

Combining newer neural networks with older AI systems could be the secret to building an AI to match or surpass human ...

Humans and artificial neural networks exhibit some similar patterns during learning

Past psychology and behavioral science studies have identified various ways in which people's acquisition of new knowledge ...
Unite.AI

Why AI Inference, Not Training, is the Next Great Engineering Challenge

For the past decade, the spotlight in artificial intelligence has been monopolized by training. The breakthroughs have largely come from massive compute clusters, trillion-parameter models, and the ...
Frontiers

Information Theory Meets Deep Neural Networks: Theory and Applications, Volume II

Information Theory Meets Deep Neural Networks: Theory and Applications. The previous volume can be viewed here: Volume I Deep Neural Networks (DNNs) have become one of the most popular research ...
IEEE

Efficient Distributed Graph Neural Network Training with Source Chunking and Moving Aggregation

Abstract: Graph neural networks (GNNs) are effective models for analyzing graph-structured data, but encounter challenges when training on large distributed graphs. Existing GNN training frameworks ...
GitHub

Simple Neural Network Models

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 ...
Sports Illustrated

Nebraska Football Featured on Big Ten Network's Training Camp Show

Nebraska football's preseason camp is nearly through the first week, but that has already come with plenty of outside coverage. On Monday, a portion of the practice was open to the local media. On ...
GitHub

MQL5 Neural Network Library

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 ...
Nasdaq

MicroCloud Hologram Inc. Unveils Innovative Noise-Resistant Deep Quantum Neural Network Architecture for Quantum AI Advancements

MicroCloud Hologram Inc. has announced the creation of a noise-resistant Deep Quantum Neural Network (DQNN) architecture, which aims to advance quantum computing and enhance the efficiency of quantum ...
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

Robust Neural Network Training for Marine Radar Target Detection Using Noisy AIS Labels

Abstract: For the neural network (NN) detector in marine radar, its superior performance relies heavily on correctly annotated large datasets bringing expensive cost. The automatic identification ...