December 26, 2019 article Open access Transfer learning enhanced physics informed neural network for phase-field modeling of fracture Theoretical and Applied Fracture Mechanics DOI: 10.1016/j.tafmec.2019.102447 Full text (OA) OpenAlex Authors 0 Author list not loaded yet. Cited by 7 stored of 909 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 Continual learning for autoregressive PDE surrogates under evolving physical regimes 2026 Machine learning for computational science and engineering article Physics and Astronomy Model Reduction and Neural Networks Open access 0 citations Transfer-learned Kolosov–Muskhelishvili informed neural networks for fracture mechanics 2026 Theoretical and Applied Fracture Mechanics article Engineering Numerical methods in engineering Open access 4 citations SPiFOL: A Spectral-based physics-informed finite operator learning for prediction of mechanical behavior of microstructures 2025 Journal of the Mechanics and Physics of Solids article Physics and Astronomy Model Reduction and Neural Networks Open access 18 citations Mixed formulation of physics‐informed neural networks for thermo‐mechanically coupled systems and heterogeneous domains 2023 International Journal for Numerical Methods in Engineering article Physics and Astronomy Model Reduction and Neural Networks Open access 98 citations 3D multi-physics uncertainty quantification using physics-based machine learning 2022 Scientific Reports article Physics and Astronomy Model Reduction and Neural Networks Open access 30 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 7 results References 0