January 01, 2026 preprint Open access Implicit Finite Difference Operator Learning for Nonlinear Time-Dependent Ordinary /Partial Differential Equations SSRN Electronic Journal DOI: 10.2139/ssrn.7174865 Full text (OA) OpenAlex Authors 0 Author list not loaded yet. Cited by 0 stored of 0 References 6 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 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 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 Theory and implementation of inelastic Constitutive Artificial Neural Networks 2024 Computer Methods in Applied Mechanics and Engineering article Engineering Elasticity and Material Modeling Open access 84 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 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 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 6 results