The aim of the workshop is to connect researchers working on this topic and surface novel research ideas and collaboration ...

The interplay between graph analytics and large language models (LLMs) represents a promising frontier for advancing ...

Despite the latest AI advancements, Large Language Models (LLMs) continue to face challenges in their integration into the ...

Discover how individual neurons in the brain learn to recognize and predict patterns in the flow of time, providing insights into the structure of time.

The AI-native workspace launches powerful Voice and AI workflows—attracting over 160,000 users to the waitlist.

Abstract: Some current researchers attempt to extend the graph neural network (GNN) on multi-view representation learning and learn the latent structure information among the data. Generally, they ...

Depending on how old you are, you might remember having to pull out a paper map to find your way around a place. Back then, ...

C. Learn more about MeidasTouch Network’s “Legal AF” podcast's new partnership with Big Auto Injury Attorneys and The Popok ...

This process is detailed in our recent publication, QirK: Question Answering via Intermediate Representation on Knowledge Graphs ... high-value machine learning and AI solutions across various ...

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 ...

Many studies have used single-cell RNA sequencing (scRNA-seq) to infer gene regulatory networks (GRNs), which are crucial for ...