March 18, 2022 article Open access Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems Computer Methods in Applied Mechanics and Engineering DOI: 10.1016/j.cma.2022.114823 Full text (OA) OpenAlex Authors 0 Author list not loaded yet. Cited by 3 stored of 721 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 Finite Operator Learning: Bridging neural operators and numerical methods for efficient parametric solution and optimization of PDEs 2025 Finite Elements in Analysis and Design article Physics and Astronomy Model Reduction and Neural Networks 10 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 3 results References 0