In a network, pairs of individual elements, or nodes, connect to each other; those connections can represent a sprawling system with myriad individual links. A hypergraph goes deeper: It gives ...

A research team from the Skoltech AI Center proposed a new neural network architecture for generating structured curved ...

GQLAlchemy is a library developed with the purpose of assisting in writing and running queries on Memgraph. GQLAlchemy supports high-level connection to Memgraph as well as modular query builder.

SAN FRANCISCO, April 16, 2025 (GLOBE NEWSWIRE) -- Operant AI, the world's only Runtime AI Defense Platform, today announced AI Gatekeeper™, a groundbreaking new product that brings end-to-end ...

Add a description, image, and links to the graph-network-simulator topic page so that developers can more easily learn about it.

Here, we showcase how our graph neural network (GNN)-based implicit solvent (GNNIS) approach can be used to rapidly compute small molecule conformational ensembles in 39 common organic solvents ...

To efficiently solve the problem, we propose a novel graph neural network (GNN)-based framework. Specifically, we first model the interactions among users and network entities using a heterogeneous ...

This dramatic contrast––visible on temperature anomaly maps––paints a surreal picture: The heart of Canada’s polar region will be milder than cities like Toronto, Hamilton, Ottawa ...

We propose GTAE-IDS, a novel unsupervised packet-based graph neural network framework aimed at early and precise anomaly detection in network traffic. GTAE-IDS employs graph embeddings to capture and ...