April 09, 2021 article Open access Efficient training of physics‐informed neural networks via importance sampling Computer-Aided Civil and Infrastructure Engineering DOI: 10.1111/mice.12685 Full text (OA) OpenAlex Authors 0 Author list not loaded yet. Cited by 2 stored of 338 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 new set of test functions for variational physics-informed neural networks in solid mechanics 2026 Journal of Computational Physics article Physics and Astronomy Model Reduction and Neural Networks Open access 0 citations Data generation framework for inverse modeling of nonlinear systems in structural dynamics applications 2023 Acta Mechanica article Engineering Control Systems and Identification Open access 5 citations 2 results References 0