Results 81 to 90 of about 5,018,820 (150)

Support for a reciprocal effects model of self-concept and academic achievement through a contrast of multidimensional and unidimensional approaches

, 2006
There is a longstanding debate in the self-concept literature surrounding the causal ordering of self-concept and academic achievement. Some researchers have argued that self-esteem has no positive impact upon performance (Baumeister, Campbell, Krueger &
Marsh, Herbert W., O'Mara, Alison J.
core  

A Dual-Channel Architecture Based on GCN and HGCN for Dynamic Link Prediction. [PDF]

Entropy (Basel)
Wu B, Zhang S, Zhou J, Xu M, Wang Q, Zeng Y, Sun K, Yuan F.   +7 more
europepmc   +1 more source

ScEnsemble: weighted hypergraph ensemble clustering for single-cell RNA sequencing. [PDF]

BMC Bioinformatics
Uncu B, Yavuz I.
europepmc   +1 more source

Graph-Based Machine Learning for Predicting Drug-Drug Interactions: A Systematic Review. [PDF]

Pharmaceuticals (Basel)
Reza MT, Kader MA, Inoubli W, Hossain MB, Islam MK.   +4 more
europepmc   +1 more source

Momentum contrast-enhanced multimodal representation learning for drug synergy prediction. [PDF]

Bioinformatics
Gu Y, Huang X, Shi L, Chen L, Duan G, Yan C.   +5 more
europepmc   +1 more source

DHGCMDA: a dual-view heterogeneous graph contrastive learning framework for miRNA-disease association type prediction. [PDF]

BMC Bioinformatics
Sun Y, Zhang F, Yan S, Kong X, Wang H, Shang J, Liu JX.   +6 more
europepmc   +1 more source

A model of multi-view contrastive hypergraph learning for predicting circRNA-disease associations. [PDF]

Sci Rep
Liu J, Yu C, Ma X, Ruan CW, Wang L.
europepmc   +1 more source

A railway surface defect detection model based on topology-enhanced feature association. [PDF]

Sci Rep
Wu Q, Abdul Rahim SB, Tang S, Azizi MAB, Wei J.   +4 more
europepmc   +1 more source

Traffic flow prediction via dynamic hypergraph learning. [PDF]

PLoS One
Wei S, Yang Y, Wang C.
europepmc   +1 more source

HYG-mol: An Interpretable Multimodal Hypergraph Framework for Molecular Property Prediction. [PDF]

Comput Struct Biotechnol J
Ma J, Yang Q, Zhang L, Liu H, Zheng Y.
europepmc   +1 more source