In the past, graph neural networks (GNNs) have shown promise in capturing the non-Euclidean ... aspects from classification and regression tasks to interpretation tasks. STIGR leverages a dynamic ...

Inspired by dynamic Graph neural networks, we propose a Group-aware Dynamic Graph Representation Learning (GDGRL) method for next POI recommendation. GDGRL connects different user sequences and ...

NetworKit is a growing open-source toolkit for large-scale network analysis.

Developed by Meta, PyTorch is a popular machine learning library that helps develop and train neural networks.

A critical procedure in diagnosing atrial fibrillation is the creation of electro-anatomic activation maps. Current methods generate these mappings from interpolation using a few sparse data points ...

AI and AR are transforming industrial IoT by enabling real-time data processing, enhancing operational efficiency, and ...

Spiking Neural Networks (SNNs) are a pathway that could potentially empower low-power event-driven neuromorphic hardware due to their spatio-temporal information ...

In 2031, it will range between $1.68 and $1.82, with an average price of $1.75. The Graph offers access to competitive and cost-efficient decentralized data sets. The network boasts a 99.99% uptime ...

config_frequentist.py: Hyperparameters for main_frequentist file. @article{shridhar2019comprehensive, title={A comprehensive guide to bayesian convolutional neural network with variational inference}, ...

Welcome to the UK's Official Charts! In addition to the Official Singles and Albums Chart, did you know the Official Charts Company compiles 50+ charts every week, spanning different genres and ...

Department of Chemical Sciences and Technologies, University of Rome, Tor Vergata, Via della Ricerca Scientifica, Rome 00133, Italy ...

The data displayed for this chart goes back to 1996, however we hope to be able to offer deeper historic information at a future point ...