{"total":14,"rows":[{"id":"2209.00517","title":"The Neural Process Family: Survey, Applications and Perspectives","created":"2022-09-01","cited_by_count":23,"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":"2207.00678","title":"Infinite-Fidelity Coregionalization for Physical Simulation","created":"2022-07-01","cited_by_count":7,"area":null},{"id":"2302.08406","title":"Entity Aware Modelling: A Survey","created":"2023-02-16","cited_by_count":4,"area":null},{"id":"2309.10231","title":"Multi-fidelity climate model parameterization for better generalization and extrapolation","created":"2023-09-19","cited_by_count":4,"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":"2301.05729","title":"GAR: Generalized Autoregression for Multi-Fidelity Fusion","created":"2023-01-13","cited_by_count":3,"area":null},{"id":"2311.05606","title":"Diffusion-Generative Multi-Fidelity Learning for Physical Simulation","created":"2023-11-09","cited_by_count":3,"area":null},{"id":"2402.10387","title":"MFBind: a Multi-Fidelity Approach for Evaluating Drug Compounds in Practical Generative Modeling","created":"2024-02-16","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":"2512.02868","title":"Assessing the performance of correlation-based multi-fidelity neural emulators","created":"2025-12-02","cited_by_count":2,"area":null},{"id":"2410.11226","title":"MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning","created":"2024-10-15","cited_by_count":1,"area":null},{"id":"2511.08231","title":"Real-Time Performance Analysis of Multi-Fidelity Residual Physics-Informed Neural Process-Based State Estimation for Robotic Systems","created":"2025-11-11","cited_by_count":0,"area":null}],"next_cursor":null}