Abstract: Graph neural networks (GNNs) have become the prevailing methodology for addressing graph data-related tasks, permeating critical domains like recommendation systems and drug development. The ...

Paper: Graph Representation of 3D CAD Models for Machining Feature Recognition With Deep Learning The MFCAD (Machining Feature CAD) dataset is a comprehensive collection of 3D CAD models with labeled ...

This repository contains the official code for our MICCAI 2025 paper, “Semantically Consistent Discrete Diffusion for 3D Biological Graph Generation.” We introduce a discrete diffusion framework that ...

Nothing kills a movie night faster than muffled dialogue and wimpy bass. Unfortunately, even expensive TVs tend to feature underpowered speakers with muddy voices and minimal rumble. That's where a ...

This dual experimental-numerical approach provides a rare, holistic view of bonded joint performance under ballistic loading, ...