{"total":15,"rows":[{"id":"2402.18377","title":"Out-of-Domain Generalization in Dynamical Systems Reconstruction","created":"2024-02-28","cited_by_count":33,"area":null},{"id":"2409.15771","title":"Zero-shot forecasting of chaotic systems","created":"2024-09-24","cited_by_count":28,"area":null},{"id":"2505.11349","title":"Context parroting: A simple but tough-to-beat baseline for foundation models in scientific machine learning","created":"2025-05-16","cited_by_count":18,"area":null},{"id":"2411.02949","title":"A scalable generative model for dynamical system reconstruction from neuroimaging data","created":"2024-11-05","cited_by_count":9,"area":null},{"id":"2503.01036","title":"Data-Efficient Kernel Methods for Learning Differential Equations and Their Solution Operators: Algorithms and Error Analysis","created":"2025-03-02","cited_by_count":7,"area":null},{"id":"2412.16588","title":"Kernel Methods for the Approximation of the Eigenfunctions of the Koopman Operator","created":"2024-12-21","cited_by_count":5,"area":null},{"id":"2408.06465","title":"Kernel Sum of Squares for Data Adapted Kernel Learning of Dynamical Systems from Data: A global optimization approach","created":"2024-08-12","cited_by_count":4,"area":null},{"id":"2311.12624","title":"Bridging Algorithmic Information Theory and Machine Learning: A New Approach to Kernel Learning","created":"2023-11-21","cited_by_count":3,"area":null},{"id":"2312.06625","title":"Decoding Mean Field Games from Population and Environment Observations By Gaussian Processes","created":"2023-12-08","cited_by_count":2,"area":null},{"id":"2502.11506","title":"Learning Surrogate Potential Mean Field Games via Gaussian Processes: A Data-Driven Approach to Ill-Posed Inverse Problems","created":"2025-02-17","cited_by_count":2,"area":null},{"id":"2405.19785","title":"Recurrent Deep Kernel Learning of Dynamical Systems","created":"2024-05-30","cited_by_count":1,"area":null},{"id":"2603.01077","title":"Kernel Methods for Stochastic Dynamical Systems with Application to Koopman Eigenfunctions: Feynman-Kac Representations and RKHS Approximation","created":"2026-03-01","cited_by_count":1,"area":null},{"id":"2603.06872","title":"Kernel Methods for Some Transport Equations with Application to Learning Kernels for the Approximation of Koopman Eigenfunctions: A Unified Approach via Variational Methods, Green's Functions and the Method of Characteristics","created":"2026-03-06","cited_by_count":1,"area":null},{"id":"2505.00909","title":"Gaussian process policy iteration with additive Schwarz acceleration for forward and inverse HJB and mean field game problems","created":"2025-05-01","cited_by_count":0,"area":null},{"id":"2604.18402","title":"Adaptive Kernel Selection for Kernelized Diffusion Maps","created":"2026-04-20","cited_by_count":0,"area":null}],"next_cursor":null}