A systematic review in Applied Intelligence introduces a two-axis taxonomy that maps how large language models enhance graph ...

AE, a graph embedding model that trains in closed form without gradient descent while outperforming conventional graph ...

Google published details of a new kind of AI based on graphs called a Graph Foundation Model (GFM) that generalizes to previously unseen graphs and delivers a three to forty times boost in precision ...

We introduce GRouNdGAN, a gene regulatory network (GRN)-guided reference-based causal implicit generative model for simulating single-cell RNA-seq data, in silico perturbation experiments, and ...

Our past columns have emphasized repeatedly that modeling is the single most important activity in mechatronics, which is becoming the design process of choice for successful multidisciplinary systems ...

Enterprise digital transformation has caused an explosion of business data -- and with it, a re-examination of data management and analytics techniques that has taken on significant implications for ...

This may come as a shock if you've first encountered knowledge graphs in Gartner's hype cycles and trends, or in the extensive coverage they are getting lately. But here it is: Knowledge graph ...

TL;DR: Using a refund workflow in ADK, we'll cover fan-out and fan-in, deterministic and agent routers, human-in-the-loop ...

Atlassian and OpenAI expand their partnership, bringing GPT-6 models into Jira and Confluence via Rovo and the Teamwork Graph.

Pretreatment CT-based radiomics and machine learning models for predicting treatment response in lung cancer: A diagnostic test accuracy meta-analysis. This is an ASCO Meeting Abstract from the 2026 ...