March 01, 2020 article Open access Physics-informed deep learning for incompressible laminar flows Theoretical and Applied Mechanics Letters DOI: 10.1016/j.taml.2020.01.039 Full text (OA) OpenAlex Authors 0 Author list not loaded yet. Cited by 4 stored of 325 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 A finite element-based physics-informed operator learning framework for spatiotemporal partial differential equations on arbitrary domains 2024 Engineering With Computers article Physics and Astronomy Model Reduction and Neural Networks Open access 39 citations Theory and implementation of inelastic Constitutive Artificial Neural Networks 2024 Computer Methods in Applied Mechanics and Engineering article Engineering Elasticity and Material Modeling Open access 84 citations Shape‐optimization of extrusion‐dies via parameterized physics‐informed neural networks 2023 PAMM article Physics and Astronomy Model Reduction and Neural Networks Open access 7 citations Effects of variational formulations on physics‐informed neural network performance in solid mechanics 2023 PAMM article Physics and Astronomy Model Reduction and Neural Networks Open access 8 citations 4 results References 0