May 05, 2021 article Open access A kd-tree-accelerated hybrid data-driven/model-based approach for poroelasticity problems with multi-fidelity multi-physics data Computer Methods in Applied Mechanics and Engineering DOI: 10.1016/j.cma.2021.113868 Full text (OA) OpenAlex Authors 0 Author list not loaded yet. Cited by 0 stored of 36 References 3 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access SO(3)-invariance of informed-graph-based deep neural network for anisotropic elastoplastic materials 2020 Computer Methods in Applied Mechanics and Engineering article Engineering Elasticity and Material Modeling Open access 129 citations Model-free data-driven computational mechanics enhanced by tensor voting 2020 Computer Methods in Applied Mechanics and Engineering article Physics and Astronomy Model Reduction and Neural Networks Open access 82 citations An offline multi‐scale unsaturated poromechanics model enabled by self‐designed/self‐improved neural networks 2021 International Journal for Numerical and Analytical Methods in Geomechanics article Engineering Soil and Unsaturated Flow 36 citations 3 results