February 16, 2022 article Open access Analyses of internal structures and defects in materials using physics-informed neural networks Science Advances DOI: 10.1126/sciadv.abk0644 Full text (OA) OpenAlex Authors 0 Author list not loaded yet. Cited by 5 stored of 396 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 Self-adaptive physics-informed quantum machine learning for solving differential equations 2024 Machine Learning Science and Technology article Computer Science Quantum Computing Algorithms and Architecture Open access 11 citations 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 Perspectives of physics-based machine learning strategies for geoscientific applications governed by partial differential equations 2023 Geoscientific model development article Physics and Astronomy Model Reduction and Neural Networks Open access 39 citations A mixed formulation for physics-informed neural networks as a potential solver for engineering problems in heterogeneous domains: Comparison with finite element method 2022 Computer Methods in Applied Mechanics and Engineering article Physics and Astronomy Model Reduction and Neural Networks Open access 12 citations A mixed formulation for physics-informed neural networks as a potential solver for engineering problems in heterogeneous domains: comparison with finite element method 2022 arXiv (Cornell University) preprint Physics and Astronomy Model Reduction and Neural Networks Open access 216 citations 5 results References 0