Results 81 to 90 of about 6,963,782 (253)
Irregularly Sampled Multivariate Time Series Classification: A Graph Learning Approach
, 2023 To date, graph-based learning methods are proven to be effective for modeling spatial and structural dependencies. However, when applied to IS-MTS, they encounter three major challenges due to the complex data characteristics of IS-MTS: 1) variable time ...
Jiang, Ting +9 more
core +1 more source
Advanced Engineering Materials, EarlyView.Geometry‐driven thermal behavior in wire‐arc additive manufacturing (WAAM) influences microstructural evolution during nonequilibrium solidification of a chemically complex Fe–Cr–Nb–W–Mo–C nanocomposite system. By comparing different deposits configurations, distinct entropy–cooling rate correlations, segregation, and carbide evolution are revealed ...
Blanca Palacios +5 more
wiley +1 more source
Federated Subgraph Learning via Global-Knowledge-Guided Node Generation
SensorsFederated graph learning (FGL) is a combination of graph representation learning and federated learning that utilizes graph neural networks (GNNs) to process complex graph-structured data while addressing data silo issues.
Yuxuan Liu +6 more
doaj +1 more source
Advanced Engineering Materials, EarlyView.A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed +6 more
wiley +1 more source
Frontiers in Energy ResearchIntroductionThe escalating integration of high-penetration renewable energy sources introduces severe dynamic stability challenges-such as low inertia and fast transients-to modern power systems, particularly in the context of Active Distribution ...
Chutao Zheng +5 more
doaj +1 more source
Towards Defect Phase Diagrams: From Research Data Management to Automated Workflows
Advanced Engineering Materials, EarlyView.A research data management infrastructure is presented for the systematic integration of heterogeneous experimental and simulation data required for defect phase diagrams. The approach combines openBIS with a companion application for large‐object storage, automated metadata extraction, provenance tracking and federated data access, thereby supporting ...
Khalil Rejiba +5 more
wiley +1 more source
spa: Semi-Supervised Semi-Parametric Graph-Based Estimation in R [PDF]
In this paper, we present an R package that combines feature-based (X) data and graph-based (G) data for prediction of the response Y . In this particular case, Y is observed for a subset of the observations (labeled) and missing for the remainder ...
Mark Culp
core
Graph-Based Semi-Supervised Learning as a Generative Model
, 2018 This paper proposes and develops a new graph-based semi-supervised learning method. Different from previous graph-based methods that are based on discriminative models, our method is essentially a generative model in that the class conditional ...
Yan Liu (5411249) +2 more
core +2 more sources
Tensorized Consensus Graph Learning for Incomplete Multi-View Clustering with Confidence Integration
Applied SciencesGraph-based multi-view clustering has gained significant attention in recent years due to its superior ability to reveal clustering structures. However, existing methods often incur high computational costs when capturing local information and overlook ...
Guangqi Jiang +3 more
doaj +1 more source
Inferring Cortical Connectivity From ECoG Signals Using Graph Signal Processing
IEEE Access, 2019 A novel method to characterize connectivity between sites in the cerebral cortex of primates is proposed in this paper. Connectivity graphs for two macaque monkeys are inferred from Electrocorticographic (ECoG) activity recorded while the animals were ...
Siddhi Tavildar +6 more
doaj +1 more source