Walkable, greener neighborhoods linked to better physical and mental health across the U.S.

A new big-data analysis of the U.S. pinpoints how urban design aids the health of city residents—especially when cities provide walking opportunities, greenery and mixed-use streets with a blend of ...
HackerNoon

The Race to Build AI’s Context Layer Is Really About Meaning

Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?

AI deciphers long-range DNA signals behind RNA splicing

Accurate RNA splicing is essential for gene expression and human health, yet predicting how DNA sequence variations affect ...
IEEE

Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow

Abstract: We present a design study of the TensorFlow Graph Visualizer, part of the TensorFlow machine intelligence platform. This tool helps users understand complex machine learning architectures by ...

Haven Safety AI Announces Product Availability in Australia, Marking First International Expansion

AI-native incident investigation and root cause analysis platform now supports Australia-specific EHS requirements, ...
IEEE

Deep Multi-Attributed-View Graph Representation Learning

Abstract: Graph representation learning aims at mapping a graph into a lower-dimensional feature space. Deep attributed graph representation, utilizing deep learning models on the graph structure and ...
EurekAlert!

Frontier AI in computational civil engineering: a review of graph, sequence, physics-informed deep learning, and beyond (2020–2025)

Researchers present a comprehensive review of frontier AI applications in computational structural analysis from 2020 to 2025, focusing on graph neural networks (GNNs), sequence-to-sequence (Seq2Seq) ...
Hacker

Riemannian Graph Learning & Structural Entropy: Deep Node Clustering in 2026

Deep Graph Clustering. Deep models have achieved state-of-the-art results in node clustering. Classic methods leverage a reconstructive loss to learn node representations, while identifying node ...
GitHub

Graph Neural Networks for Tabular Data Learning (GNN4TDL)

The deep learning-based approaches to Tabular Data Learning (TDL), classification and regression, have shown competing performance, compared to their conventional counterparts. However, the latent ...