Results 141 to 150 of about 228,260 (299)
Improving Network Representation Learning via Dynamic Random Walk, Self-Attention and Vertex Attributes-Driven Laplacian Space Optimization. [PDF]
Entropy (Basel), 2022 Hu S +6 more
europepmc +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objectives Focal cortical dysplasia (FCD) is the most common etiology of drug‐resistant epilepsy in children. Focal to bilateral tonic–clonic seizures (FBTCS) mark a high risk of drug‐resistant epilepsy and involve thalamocortical circuitry in their generation and propagation.
Hua Xie +8 more
wiley +1 more source
SME leaders’ learning in networked learning : an actor-network theory and communities of practice theory informed analysis [PDF]
, 2011 This thesis brings a Communities of Practice perspective together with Actor-network theory to provide a rich understanding of the social learning processes of SME leaders within a networked learning programme.
Hodgson, Vivien +3 more
core
fdata-02-00002-g0003_Deep Representation Learning for Social Network Analysis.tif
, 2020 Social network analysis is an important problem in data mining. A fundamental step for analyzing social networks is to encode network data into low-dimensional representations, i.e., network embeddings, so that the network topology structure and other ...
Qiaoyu Tan (8541435) +2 more
core +1 more source
Towards Semantically-Rich Spatial Network Representation Learning via Automated Feature Topic Pairing. [PDF]
Front Big Data, 2021 Wang D +5 more
europepmc +1 more source
Arthritis Care &Research, EarlyView.Objective A patient‐centered approach for chronic disease management, including systemic lupus erythematosus (SLE), aligns treatment with patients’ values and preferences, leading to improved outcomes. This paper summarizes how patient experiences, perspectives, and priorities informed the American College of Rheumatology (ACR) 2024 Lupus Nephritis (LN)
Shivani Garg +20 more
wiley +1 more source
fdata-02-00002_Deep Representation Learning for Social Network Analysis.pdf
, 2020 Social network analysis is an important problem in data mining. A fundamental step for analyzing social networks is to encode network data into low-dimensional representations, i.e., network embeddings, so that the network topology structure and other ...
Qiaoyu Tan (8541435) +2 more
core +1 more source
Arthritis Care &Research, EarlyView.Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos +2 more
wiley +1 more source
Heterogeneous Network Representation Learning: A Unified Framework with Survey and Benchmark. [PDF]
IEEE Trans Knowl Data Eng, 2022 Yang C, Xiao Y, Zhang Y, Sun Y, Han J.
europepmc +1 more source
A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems
International Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam +2 more
wiley +1 more source