Graph representation learning has been extensively studied in recent years. It has been proven effective in network analysis and mining tasks such as node classification and link prediction. Learning ...

First, the model constructs a scalable neural network with shared hidden layers for exploring a low-dimensional representations of all views. Second, the quality of representation matrix is evaluated ...

Syllabus: The NTA has put the official JEE Main 2026 Syllabus online on their website: jeemain.nta.nic.in. If you're planning ...

By learning the relevant features of clinical images along with the relationships between them, the neural network can outperform more traditional methods.

This important study presents a new method for longitudinally tracking cells in two-photon imaging data that addresses the specific challenges of imaging neurons in the developing cortex. It provides ...

Graphs, visual representations outlining the relationships between different entities, concepts or variables, can be very effective in summarizing complex patterns and information. Past psychology ...

The rapid identification of respiratory virus outbreaks is needed to enable rational and effective public health interventions. We developed new quantitative approaches for simultaneous ...

In its official statement, the agency noted, “The National Testing Agency (NTA) is in receipt of various representations from ...

The Center for Transyouth Health and Development at Children’s Hospital Los Angeles will close its doors July 22.

Self-supervised Representation Learning for Neuronal Morphologies This repository contains code to the paper Self-Supervised Graph Representation Learning for Neuronal Morphologies by M.A. Weis, L.