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 ...

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.

Tana, the all-in-one workspace that naturally integrates AI into everyday work, announced a $14 million Series A round led by ...

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 ...

Data4Cure today announced an ongoing multi-year partnership with Pfizer, aimed at leveraging advanced analytics and knowledge graph AI to drive innovation in Pfizer's drug discovery and development ...