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Machine Learning, Low-Rank Approximations and Reduced Order Modeling in Computational Mechanics
| Machine Learning, Low-Rank Approximations and Reduced Order Modeling in Computational Mechanics |
| Autore | Fritzen Felix |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (254 p.) |
| Soggetto non controllato |
supervised machine learning
proper orthogonal decomposition (POD) PGD compression stabilization nonlinear reduced order model gappy POD symplectic model order reduction neural network snapshot proper orthogonal decomposition 3D reconstruction microstructure property linkage nonlinear material behaviour proper orthogonal decomposition reduced basis ECSW geometric nonlinearity POD model order reduction elasto-viscoplasticity sampling surrogate modeling model reduction enhanced POD archive modal analysis low-rank approximation computational homogenization artificial neural networks unsupervised machine learning large strain reduced-order model proper generalised decomposition (PGD) a priori enrichment elastoviscoplastic behavior error indicator computational homogenisation empirical cubature method nonlinear structural mechanics reduced integration domain model order reduction (MOR) structure preservation of symplecticity heterogeneous data reduced order modeling (ROM) parameter-dependent model data science Hencky strain dynamic extrapolation tensor-train decomposition hyper-reduction empirical cubature randomised SVD machine learning inverse problem plasticity proper symplectic decomposition (PSD) finite deformation Hamiltonian system DEIM GNAT |
| ISBN | 3-03921-410-1 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367759403321 |
Fritzen Felix
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Systems Analytics and Integration of Big Omics Data
| Systems Analytics and Integration of Big Omics Data |
| Autore | Hardiman Gary |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (202 p.) |
| Soggetto non controllato |
precision medicine informatics
drug sensitivity chromatin modification cell lines biocuration neurodegeneration multivariate analysis artificial intelligence epigenetics missing data sequencing clinical data class imbalance integrative analytics algorithm development for network integration deep phenotype non-omics data feature selection Gene Ontology miRNA-gene expression networks omics data plot visualization Alzheimer's disease tissue classification epidemiological data proteomic analysis genotype RNA expression indirect effect multi-omics dementia multiomics integration data integration phenomics network topology analysis challenges transcriptome enrichment analysis regulatory genomics scalability heterogeneous data systemic lupus erythematosus database microtubule-associated protein tau disease variants genomics joint modeling distance correlation annotation phenotype direct effect curse of dimensionality gene-environment interactions logic forest machine learning KEGG pathways multivariate causal mediation amyloid-beta bioinformatics pipelines support vector machine pharmacogenomics candidate genes tissue-specific expressed genes cognitive impairment causal inference |
| ISBN | 3-03928-745-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910404089603321 |
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Hardiman Gary
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| MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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