{"total":35,"rows":[{"id":"2202.06137","title":"MIONet: Learning multiple-input operators via tensor product","created":"2022-02-12","cited_by_count":181,"area":null},{"id":"2207.05748","title":"Physics-Informed Deep Neural Operator Networks","created":"2022-07-08","cited_by_count":113,"area":null},{"id":"2204.06684","title":"Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of nanoscale heat transport","created":"2022-04-14","cited_by_count":92,"area":null},{"id":"2203.08205","title":"Learning Deep Implicit Fourier Neural Operators (IFNOs) with Applications to Heterogeneous Material Modeling","created":"2022-03-15","cited_by_count":65,"area":null},{"id":"2208.13273","title":"Blending Neural Operators and Relaxation Methods in PDE Numerical Solvers","created":"2022-08-28","cited_by_count":54,"area":null},{"id":"2203.00003","title":"Interfacing Finite Elements with Deep Neural Operators for Fast Multiscale Modeling of Mechanics Problems","created":"2022-02-25","cited_by_count":48,"area":null},{"id":"2305.00478","title":"Domain Agnostic Fourier Neural Operators","created":"2023-04-30","cited_by_count":38,"area":null},{"id":"2204.12670","title":"SVD Perspectives for Augmenting DeepONet Flexibility and Interpretability","created":"2022-04-27","cited_by_count":35,"area":null},{"id":"2212.14365","title":"INO: Invariant Neural Operators for Learning Complex Physical Systems with Momentum Conservation","created":"2022-12-29","cited_by_count":28,"area":null},{"id":"2312.05410","title":"Rethinking materials simulations: Blending direct numerical simulations with neural operators","created":"2023-12-08","cited_by_count":25,"area":null},{"id":"2309.15421","title":"Deep Learning in Deterministic Computational Mechanics","created":"2023-09-27","cited_by_count":21,"area":null},{"id":"2204.00205","title":"A Physics-Guided Neural Operator Learning Approach to Model Biological Tissues from Digital Image Correlation Measurements","created":"2022-04-01","cited_by_count":20,"area":null},{"id":"2401.06070","title":"Peridynamic Neural Operators: A Data-Driven Nonlocal Constitutive Model for Complex Material Responses","created":"2024-01-11","cited_by_count":18,"area":null},{"id":"2303.07647","title":"Recent Advances and Applications of Machine Learning in Experimental Solid Mechanics: A Review","created":"2023-03-14","cited_by_count":15,"area":null},{"id":"2405.12465","title":"A finite element-based physics-informed operator learning framework for spatiotemporal partial differential equations on arbitrary domains","created":"2024-05-21","cited_by_count":15,"area":null},{"id":"2205.03780","title":"Neural operator learning of heterogeneous mechanobiological insults contributing to aortic aneurysms","created":"2022-05-08","cited_by_count":14,"area":null},{"id":"2503.03178","title":"Active operator learning with predictive uncertainty quantification for partial differential equations","created":"2025-03-05","cited_by_count":12,"area":null},{"id":"2301.12095","title":"MetaNO: How to Transfer Your Knowledge on Learning Hidden Physics","created":"2023-01-28","cited_by_count":10,"area":null},{"id":"2307.04569","title":"Interpreting and generalizing deep learning in physics-based problems with functional linear models","created":"2023-07-10","cited_by_count":9,"area":null},{"id":"2301.13331","title":"Neural Operator: Is data all you need to model the world? An insight into the paradigm of data-driven scientific ML","created":"2023-01-30","cited_by_count":8,"area":null},{"id":"2305.03184","title":"A Generative Modeling Framework for Inferring Families of Biomechanical Constitutive Laws in Data-Sparse Regimes","created":"2023-05-04","cited_by_count":8,"area":null},{"id":"2208.09889","title":"G2{\\Phi}net: Relating Genotype and Biomechanical Phenotype of Tissues with Deep Learning","created":"2022-08-21","cited_by_count":6,"area":null},{"id":"2308.09274","title":"A hybrid Decoder-DeepONet operator regression framework for unaligned observation data","created":"2023-08-18","cited_by_count":6,"area":null},{"id":"2302.01538","title":"DCEM: A deep complementary energy method for solid mechanics","created":"2023-02-03","cited_by_count":5,"area":null},{"id":"2505.20349","title":"FD-Bench: A Modular and Fair Benchmark for Data-driven Fluid Simulation","created":"2025-05-25","cited_by_count":5,"area":null},{"id":"2403.18597","title":"Heterogeneous Peridynamic Neural Operators: Discover Biotissue Constitutive Law and Microstructure From Digital Image Correlation Measurements","created":"2024-03-27","cited_by_count":4,"area":null},{"id":"2406.03407","title":"Physics and geometry informed neural operator network with application to acoustic scattering","created":"2024-06-02","cited_by_count":3,"area":null},{"id":"2503.17402","title":"Enhanced Vascular Flow Simulations in Aortic Aneurysm via Physics-Informed Neural Networks and Deep Operator Networks","created":"2025-03-19","cited_by_count":3,"area":null},{"id":"2510.15651","title":"Deep Neural ODE Operator Networks for PDEs","created":"2025-10-17","cited_by_count":3,"area":null},{"id":"2311.13812","title":"Mechanical Characterization and Inverse Design of Stochastic Architected Metamaterials Using Neural Operators","created":"2023-11-23","cited_by_count":2,"area":null},{"id":"2608.27256","title":"Enforcing Dirichlet Boundary Conditions in Operator Learning","created":"2026-08-27","cited_by_count":1,"area":null},{"id":"2311.02328","title":"An Operator Learning Framework for Spatiotemporal Super-resolution of Scientific Simulations","created":"2023-11-04","cited_by_count":0,"area":null},{"id":"2603.01420","title":"Tackling multiphysics problems via finite element-guided physics-informed operator learning","created":"2026-03-02","cited_by_count":0,"area":null},{"id":"2603.06939","title":"Physics-Consistent Neural Networks for Learning Deformation and Director Fields in Microstructured Media with Loss-Based Validation Criteria","created":"2026-03-06","cited_by_count":0,"area":null},{"id":"2608.27883","title":"Beyond Pairwise Graphs in Science: Hypergraph Adaptive Wavelet Operators for Parametric PDEs","created":"2026-08-28","cited_by_count":0,"area":null}],"next_cursor":null}