Global ETD Search

Cross Domain Reasoning Based on Graph Deep Learning

Chowdhury, Tanmoy2023

gmu

MACHINE LEARNING FOR TEMPORAL HETEROGENEOUS GRAPHS: PREDICTIVE METHODS, INTERPRETABILITY AND APPLICATIONS.

DILEO, MANUELUniversità degli Studi di Milano2025

… predictive methods for temporal heterogeneous graphs by integrating modeling and tools from network science and graph deep learning. We introduce discrete-time graph learning architectures based on Graph Neural Networks (GNNs) and linear scoring functions tailored for forecasting dynamic, …

milano Repository record for MACHINE LEARNING FOR TEMPORAL HETEROGENEOUS GRAPHS: PREDICTIVE METHODS, INTERPRETABILITY AND APPLICATIONS. (opens in a new tab)

Real-time Topology-Aware Augmented Reality

Gao, QinghongBournemouth University2024

… of scenes. Topological structures, such as graphs, can provide information on the relationship between point clouds to improve the quality of point cloud-based real-world 3D map reconstruc- tions for topology-aware AR systems. The reconstructed 3D maps provide information to improve the …

bournemouth Repository record for Real-time Topology-Aware Augmented Reality (opens in a new tab)

Efficient Deep Learning Systems for Visual Perception on the Edge

Yang, ShangMassachusetts Institute of Technology2025

Deep learning for visual perception on edge devices has become increasingly critical, driven by emerging applications in autonomous driving and AR/VR. Typically, sparse convolution on 3D point clouds and Visual Language Models (VLMs) for image processing are two important methods for visual …

mit Repository record for Efficient Deep Learning Systems for Visual Perception on the Edge (opens in a new tab)

BEYOND LOCAL NEIGHBORHOODS: LEVERAGING INFORMATIVE NODES FOR IMPROVED GRAPH NEURAL NETWORKS PERFORMANCE

Liang, PeiyuTemple University. Libraries2024

… and scientific domains, can be represented as graphs, where entities are depicted as nodes and their relationships as edges. To analyze the properties of individual entities (node classification) or the community as a whole (graph classification), graph neural networks (GNNs) serve as a …

temple Repository record for BEYOND LOCAL NEIGHBORHOODS: LEVERAGING INFORMATIVE NODES FOR IMPROVED GRAPH NEURAL NETWORKS PERFORMANCE (opens in a new tab)

Empowering graph intelligence via natural and artificial dynamics

Fu, DongqiUniversity of Illinois at Urbana-Champaign2024

Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-02-04 without embargo terms

uiuc Repository record for Empowering graph intelligence via natural and artificial dynamics (opens in a new tab)

Automatic Extraction of Computer Science Concept Phrases Using a Hybrid Machine Learning Paradigm

Jahin, S M Abrar2022

… adding all concepts and terms to the knowledge graph would be a challenging endeavor. Cre- ating a system that automatically adds all computer science domain terms to the knowledge graph would be a straightforward solution to the issue. We have identified knowledge graph use cases for the …

iupui Repository record for Automatic Extraction of Computer Science Concept Phrases Using a Hybrid Machine Learning Paradigm (opens in a new tab)