{"total":30,"rows":[{"id":"2208.03115","title":"Multi-fidelity surrogate modeling using long short-term memory networks","created":"2022-08-05","cited_by_count":18,"area":null},{"id":"2309.00325","title":"Multi-fidelity reduced-order surrogate modeling","created":"2023-09-01","cited_by_count":18,"area":null},{"id":"2110.13530","title":"An extended physics informed neural network for preliminary analysis of parametric optimal control problems","created":"2021-10-26","cited_by_count":16,"area":null},{"id":"2206.04872","title":"Multi-fidelity Hierarchical Neural Processes","created":"2022-06-10","cited_by_count":15,"area":null},{"id":"2302.12682","title":"A DeepONet multi-fidelity approach for residual learning in reduced order modeling","created":"2023-02-24","cited_by_count":14,"area":null},{"id":"2402.18846","title":"Multi-Fidelity Residual Neural Processes for Scalable Surrogate Modeling","created":"2024-02-29","cited_by_count":13,"area":null},{"id":"2305.04392","title":"Disentangled Multi-Fidelity Deep Bayesian Active Learning","created":"2023-05-07","cited_by_count":11,"area":null},{"id":"2406.03569","title":"GFN: A graph feedforward network for resolution-invariant reduced operator learning in multifidelity applications","created":"2024-06-05","cited_by_count":10,"area":null},{"id":"2410.14764","title":"Multifidelity Kolmogorov-Arnold Networks","created":"2024-10-18","cited_by_count":9,"area":null},{"id":"2303.11577","title":"Feature-adjacent multi-fidelity physics-informed machine learning for partial differential equations","created":"2023-03-21","cited_by_count":8,"area":null},{"id":"2205.05187","title":"Multifidelity data fusion in convolutional encoder/decoder networks","created":"2022-05-10","cited_by_count":5,"area":null},{"id":"2310.03572","title":"Residual Multi-Fidelity Neural Network Computing","created":"2023-10-05","cited_by_count":5,"area":null},{"id":"2407.15110","title":"Practical multi-fidelity machine learning: fusion of deterministic and Bayesian models","created":"2024-07-21","cited_by_count":4,"area":null},{"id":"2403.08627","title":"Multifidelity linear regression for scientific machine learning from scarce data","created":"2024-03-13","cited_by_count":3,"area":null},{"id":"2407.05684","title":"Multi-Fidelity Bayesian Neural Network for Uncertainty Quantification in Transonic Aerodynamic Loads","created":"2024-07-08","cited_by_count":2,"area":null},{"id":"2510.13762","title":"Progressive multi-fidelity learning with neural networks for physical system predictions","created":"2025-10-15","cited_by_count":2,"area":null},{"id":"2603.12870","title":"Surrogates for Physics-based and Data-driven Modelling of Parametric Systems: Review and New Perspectives","created":"2026-03-13","cited_by_count":2,"area":null},{"id":"2506.11683","title":"On the performance of multi-fidelity and reduced-dimensional neural emulators for inference of physiological boundary conditions","created":"2025-06-13","cited_by_count":1,"area":null},{"id":"2512.05241","title":"Bridging quantum and classical computing for partial differential equations through multifidelity machine learning","created":"2025-12-04","cited_by_count":1,"area":null},{"id":"2512.16430","title":"Multi-Fidelity Delayed Acceptance: hierarchical MCMC sampling for Bayesian inverse problems combining multiple solvers through deep neural networks","created":"2025-12-18","cited_by_count":1,"area":null},{"id":"2603.14143","title":"Multifidelity Surrogate Modeling of Depressurized Loss of Forced Cooling in High-temperature Gas Reactors","created":"2026-03-14","cited_by_count":1,"area":null},{"id":"2606.15690","title":"Multi-Fidelity SINDy: Sparse Discovery of Nonlinear Dynamical Systems with Fidelity-Weighted Measurements","created":"2026-06-14","cited_by_count":1,"area":null},{"id":"2301.09483","title":"An iterative multi-fidelity approach for model order reduction of multi-dimensional input parametric PDE systems","created":"2023-01-23","cited_by_count":0,"area":null},{"id":"2306.06904","title":"Differentiable Multi-Fidelity Fusion: Efficient Learning of Physics Simulations with Neural Architecture Search and Transfer Learning","created":"2023-06-12","cited_by_count":0,"area":null},{"id":"2411.03598","title":"Open-Source High-Speed Flight Surrogate Modeling Framework","created":"2024-11-06","cited_by_count":0,"area":null},{"id":"2508.08517","title":"Projection-based multifidelity linear regression for data-scarce applications","created":"2025-08-11","cited_by_count":0,"area":null},{"id":"2512.13069","title":"Multi-fidelity aerodynamic data fusion by autoencoder transfer learning","created":"2025-12-15","cited_by_count":0,"area":null},{"id":"2601.10031","title":"FilDeep: Learning Large Deformations of Elastic-Plastic Solids with Multi-Fidelity Data","created":"2026-01-15","cited_by_count":0,"area":null},{"id":"2602.01176","title":"Multi-Fidelity Physics-Informed Neural Networks with Bayesian Uncertainty Quantification and Adaptive Residual Learning for Efficient Solution of Parametric Partial Differential Equations","created":"2026-02-01","cited_by_count":0,"area":null},{"id":"2608.16873","title":"A Data-Efficient Analytical Prior Machine Learning Framework for Sound Reduction Frequency Prediction in Helmholtz Resonators","created":"2026-08-17","cited_by_count":0,"area":null}],"next_cursor":null}