2025
SuperGLUE facilitates an explainable training framework for multi-modal data analysis
Liu T, Zhao J, Zhao H. SuperGLUE facilitates an explainable training framework for multi-modal data analysis. Cell Reports Methods 2025, 5: 101167. PMID: 40914154, DOI: 10.1016/j.crmeth.2025.101167.Peer-Reviewed Original ResearchConceptsData integrationProbabilistic deep learningMulti-modal data analysisInference of gene regulatory networksMulti-modal data integrationDeep learningGene regulatory networksTraining frameworkBaseline modelRegulatory networksComplex biological systemsRegulatory relationshipsSensing dataCell statesGlobal structureArea of active researchActive researchOmicsBiological featuresScalable methodFrameworkBiological systemsStatistical modelNetworkBiological linkages
2024
Bayesian subtyping for multi-state brain functional connectome with application on preadolescent brain cognition
Chen T, Zhao H, Tan C, Constable T, Yip S, Zhao Y. Bayesian subtyping for multi-state brain functional connectome with application on preadolescent brain cognition. Biostatistics 2024, 26: kxae045. PMID: 39656842, PMCID: PMC11823269, DOI: 10.1093/biostatistics/kxae045.Peer-Reviewed Original ResearchAdolescent Brain Cognitive DevelopmentVariational inference algorithmApproximate posterior inferenceFunctional connectivityMultiple cognitive statesInference algorithmExtensive simulationsNetwork topologyNetwork featuresFunctional network patternsBrain functional connectomeBrain functional connectivityEstimation accuracySubgroups of individualsNeurobiological heterogeneityCognitive profileCognitive statesConverging evidencePosterior inferenceDetection alternativesNeuroscience literatureBrain cognitionFunctional connectomeNetworkCognitive development
2023
None-Exemplar Class Incremental Learning with Feature Contrast and Expanded Distillation
Wang Y, Zhao H. None-Exemplar Class Incremental Learning with Feature Contrast and Expanded Distillation. 2023, 00: 1-8. DOI: 10.1109/icarce59252.2024.10492612.Peer-Reviewed Original Research
2022
Garbage Image Classification Based on Improved Residual Neural Networks
Zhao L, Zhao H. Garbage Image Classification Based on Improved Residual Neural Networks. 2022, 00: 7-13. DOI: 10.1109/icicml57342.2022.10009851.Peer-Reviewed Original ResearchConvolutional block attention moduleClassification accuracyAttention mechanismImproved residual neural networkGarbage image classificationGarbage classification algorithmResidual neural networkGarbage imagesImage classificationResNet34 networkAttention moduleClassification performanceFeature informationNeural networkClassification algorithmsArtificial network modelNetwork modelTarget informationResNet34ClassificationNetworkGarbageInformationAlgorithmAccuracy
2017
Network Clustering Analysis Using Mixture Exponential-Family Random Graph Models and Its Application in Genetic Interaction Data
Wang Y, Fang H, Yang D, Zhao H, Deng M. Network Clustering Analysis Using Mixture Exponential-Family Random Graph Models and Its Application in Genetic Interaction Data. IEEE Transactions On Computational Biology And Bioinformatics 2017, 16: 1743-1752. PMID: 28858811, DOI: 10.1109/tcbb.2017.2743711.Peer-Reviewed Original ResearchConceptsExponential-family random graph modelsRandom graph modelsGraph modelStatistical network modelsHeterogeneity of networksLarge-scale genetic interaction networksReal social networksERGM parametersSubset of nodesOnline graphStatistical modelData sizeObserved networkEM algorithmNetwork informationGraph nodesMixture problemSocial networksFlexible wayNetwork modelNetwork clustersClassical methodsIncredible setInteraction dataNetworkOn Joint Estimation of Gaussian Graphical Models for Spatial and Temporal Data
Lin Z, Wang T, Yang C, Zhao H. On Joint Estimation of Gaussian Graphical Models for Spatial and Temporal Data. Biometrics 2017, 73: 769-779. PMID: 28099997, PMCID: PMC5515703, DOI: 10.1111/biom.12650.Peer-Reviewed Original ResearchConceptsGaussian graphical modelsTemporal dataGraphical modelsComplex data structuresJoint estimationMarkov random field modelRandom field modelParallel computingSelection consistencyData structureStatistical inferenceNeighborhood selection methodTemporal dependenciesEfficient algorithmIndividual networksMultiple groupsSpatial dataModel convergesNetwork estimationField modelSelection methodNetworkPosterior probabilitySimulation studyImproved estimation
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