{"total":32,"rows":[{"id":"2103.09360","title":"Towards physically consistent data-driven weather forecasting: Integrating data assimilation with equivariance-preserving deep spatial transformers","created":"2021-03-16","cited_by_count":15,"area":null},{"id":"2104.12506","title":"Bridging observation, theory and numerical simulation of the ocean using Machine Learning","created":"2021-04-26","cited_by_count":15,"area":null},{"id":"2311.11798","title":"Neural Dynamical Operator: Continuous Spatial-Temporal Model with Gradient-Based and Derivative-Free Optimization Methods","created":"2023-11-20","cited_by_count":14,"area":null},{"id":"2101.03906","title":"Scaling Up Bayesian Uncertainty Quantification for Inverse Problems using Deep Neural Networks","created":"2021-01-11","cited_by_count":10,"area":null},{"id":"2307.07882","title":"Gradient-free training of neural ODEs for system identification and control using ensemble Kalman inversion","created":"2023-07-15","cited_by_count":9,"area":null},{"id":"2104.03384","title":"Ensemble Inference Methods for Models With Noisy and Expensive Likelihoods","created":"2021-04-07","cited_by_count":8,"area":null},{"id":"2208.03246","title":"Non-Asymptotic Analysis of Ensemble Kalman Updates: Effective Dimension and Localization","created":"2022-08-05","cited_by_count":7,"area":null},{"id":"2407.00584","title":"Hyperparameter Optimization for Randomized Algorithms: A Case Study on Random Features","created":"2024-06-30","cited_by_count":7,"area":null},{"id":"2208.04506","title":"Second Order Ensemble Langevin Method for Sampling and Inverse Problems","created":"2022-08-09","cited_by_count":6,"area":null},{"id":"2303.07392","title":"Efficient Bayesian Physics Informed Neural Networks for Inverse Problems via Ensemble Kalman Inversion","created":"2023-03-13","cited_by_count":6,"area":null},{"id":"2310.19385","title":"Gradient-free online learning of subgrid-scale dynamics with neural emulators","created":"2023-10-30","cited_by_count":5,"area":null},{"id":"2502.05372","title":"Active Learning of Model Discrepancy with Bayesian Experimental Design","created":"2025-02-07","cited_by_count":5,"area":null},{"id":"2311.10665","title":"Online Calibration of Deep Learning Sub-Models for Hybrid Numerical Modeling Systems","created":"2023-11-17","cited_by_count":4,"area":null},{"id":"2403.03444","title":"Uncertainty quantification for deeponets with ensemble kalman inversion","created":"2024-03-06","cited_by_count":4,"area":null},{"id":"2309.11490","title":"Flow Annealed Kalman Inversion for Gradient-Free Inference in Bayesian Inverse Problems","created":"2023-09-20","cited_by_count":2,"area":null},{"id":"2312.00907","title":"Extreme Event Prediction with Multi-agent Reinforcement Learning-based Parametrization of Atmospheric and Oceanic Turbulence","created":"2023-12-01","cited_by_count":2,"area":null},{"id":"2411.15265","title":"Derivative-Free Diffusion Manifold-Constrained Gradient for Unified XAI","created":"2024-11-22","cited_by_count":2,"area":null},{"id":"2501.08501","title":"Scalable Bayesian Physics-Informed Kolmogorov-Arnold Networks","created":"2025-01-15","cited_by_count":2,"area":null},{"id":"2504.20319","title":"Bayesian Experimental Design for Model Discrepancy Calibration: An Auto-Differentiable Ensemble Kalman Inversion Approach","created":"2025-04-29","cited_by_count":2,"area":null},{"id":"2211.00601","title":"A unified method of data assimilation and turbulence modeling for separated flows at high Reynolds numbers","created":"2022-11-01","cited_by_count":1,"area":null},{"id":"2402.06682","title":"Private Knowledge Sharing in Distributed Learning: A Survey","created":"2024-02-08","cited_by_count":1,"area":null},{"id":"2411.14106","title":"Adjoint-based online learning of two-layer quasi-geostrophic baroclinic turbulence","created":"2024-11-21","cited_by_count":1,"area":null},{"id":"2501.08779","title":"Nesterov Acceleration for Ensemble Kalman Inversion and Variants","created":"2025-01-15","cited_by_count":1,"area":null},{"id":"2204.13089","title":"Variational Kalman Filtering with Hinf-Based Correction for Robust Bayesian Learning in High Dimensions","created":"2022-04-27","cited_by_count":0,"area":null},{"id":"2301.12640","title":"Reweighted Interacting Langevin Diffusions: an Accelerated Sampling Methodfor Optimization","created":"2023-01-30","cited_by_count":0,"area":null},{"id":"2309.04742","title":"Affine Invariant Ensemble Transform Methods to Improve Predictive Uncertainty in Neural Networks","created":"2023-09-09","cited_by_count":0,"area":null},{"id":"2412.05667","title":"Training neural networks without backpropagation using particles","created":"2024-12-07","cited_by_count":0,"area":null},{"id":"2502.03048","title":"The Ensemble Kalman Update is an Empirical Matheron Update","created":"2025-02-05","cited_by_count":0,"area":null},{"id":"2503.15160","title":"Nonlinear Bayesian Update via Ensemble Kernel Regression with Clustering and Subsampling","created":"2025-03-19","cited_by_count":0,"area":null},{"id":"2505.02590","title":"Ensemble Kalman filter for uncertainty in human language comprehension","created":"2025-05-05","cited_by_count":0,"area":null},{"id":"2601.16425","title":"Bayesian Experimental Design for Model Discrepancy Calibration: A Rivalry between Kullback--Leibler Divergence and Wasserstein Distance","created":"2026-01-23","cited_by_count":0,"area":null},{"id":"2605.07060","title":"Functional-prior-based approaches to Bayesian PDE-constrained inversion using physics-informed neural networks","created":"2026-05-08","cited_by_count":0,"area":null}],"next_cursor":null}