January 28, 2022 article Open access A physics-informed variational DeepONet for predicting crack path in quasi-brittle materials Computer Methods in Applied Mechanics and Engineering DOI: 10.1016/j.cma.2022.114587 Full text (OA) OpenAlex Authors 0 Author list not loaded yet. Cited by 11 stored of 427 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 Tackling multiphysics problems via finite element guided physics-informed operator learning 2026 Results in Engineering article Physics and Astronomy Model Reduction and Neural Networks Open access 2 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 Attention-Enhanced Damage Prediction in Electrode Materials From Simulation Video Sequences 2026 IEEE Transactions on Automation Science and Engineering article Engineering Advanced Battery Technologies Research Open access 0 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 A Finite Operator Learning Technique for Mapping the Elastic Properties of Microstructures to Their Mechanical Deformations 2024 International Journal for Numerical Methods in Engineering article Physics and Astronomy Model Reduction and Neural Networks Open access 27 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 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 On the order of derivation in the training of physics-informed neural networks: case studies for non-uniform beam structures 2023 Acta Mechanica article Physics and Astronomy Model Reduction and Neural Networks 25 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 11 results References 0