{"total":49,"rows":[{"id":"2209.14855","title":"Continuous PDE Dynamics Forecasting with Implicit Neural Representations","created":"2022-09-29","cited_by_count":73,"area":null},{"id":"2306.04406","title":"Generalized Teacher Forcing for Learning Chaotic Dynamics","created":"2023-06-07","cited_by_count":58,"area":null},{"id":"2306.01187","title":"Training neural operators to preserve invariant measures of chaotic attractors","created":"2023-06-01","cited_by_count":46,"area":null},{"id":"2402.18377","title":"Out-of-Domain Generalization in Dynamical Systems Reconstruction","created":"2024-02-28","cited_by_count":33,"area":null},{"id":"2504.19496","title":"DISCO: learning to DISCover an evolution Operator for multi-physics-agnostic prediction","created":"2025-04-28","cited_by_count":21,"area":null},{"id":"2505.13192","title":"True Zero-Shot Inference of Dynamical Systems Preserving Long-Term Statistics","created":"2025-05-19","cited_by_count":20,"area":null},{"id":"2410.03437","title":"Zebra: In-Context Generative Pretraining for Solving Parametric PDEs","created":"2024-10-04","cited_by_count":16,"area":null},{"id":"2410.04814","title":"Learning Interpretable Hierarchical Dynamical Systems Models from Time Series Data","created":"2024-10-07","cited_by_count":15,"area":null},{"id":"2403.17728","title":"Masked Autoencoders are PDE Learners","created":"2024-03-26","cited_by_count":14,"area":null},{"id":"2403.19507","title":"SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations","created":"2024-03-28","cited_by_count":14,"area":null},{"id":"2406.08473","title":"Strategies for Pretraining Neural Operators","created":"2024-06-12","cited_by_count":14,"area":null},{"id":"2312.00477","title":"Interpretable Meta-Learning of Physical Systems","created":"2023-12-01","cited_by_count":11,"area":null},{"id":"2602.00884","title":"Test-time Generalization for Physics through Neural Operator Splitting","created":"2026-01-31","cited_by_count":10,"area":null},{"id":"2405.02154","title":"Neural Context Flows for Meta-Learning of Dynamical Systems","created":"2024-05-03","cited_by_count":9,"area":null},{"id":"2410.05454","title":"Meta-Dynamical State Space Models for Integrative Neural Data Analysis","created":"2024-10-07","cited_by_count":8,"area":null},{"id":"2410.23889","title":"GEPS: Boosting Generalization in Parametric PDE Neural Solvers through Adaptive Conditioning","created":"2024-10-31","cited_by_count":7,"area":null},{"id":"2206.13336","title":"Continual Learning of Dynamical Systems with Competitive Federated Reservoir Computing","created":"2022-06-27","cited_by_count":6,"area":null},{"id":"2303.03181","title":"MetaPhysiCa: OOD Robustness in Physics-informed Machine Learning","created":"2023-03-06","cited_by_count":6,"area":null},{"id":"2212.03857","title":"Phase2vec: Dynamical systems embedding with a physics-informed convolutional network","created":"2022-12-07","cited_by_count":5,"area":null},{"id":"2502.04495","title":"Discovering Physics Laws of Dynamical Systems via Invariant Function Learning","created":"2025-02-06","cited_by_count":5,"area":null},{"id":"2506.01153","title":"Weight-Space Linear Recurrent Neural Networks","created":"2025-06-01","cited_by_count":5,"area":null},{"id":"2212.01168","title":"Towards Cross Domain Generalization of Hamiltonian Representation via Meta Learning","created":"2022-12-02","cited_by_count":3,"area":null},{"id":"2302.05942","title":"SpReME: Sparse Regression for Multi-Environment Dynamic Systems","created":"2023-02-12","cited_by_count":2,"area":null},{"id":"2303.15827","title":"CONFIDE: Contextual Finite Differences Modelling of PDEs","created":"2023-03-28","cited_by_count":2,"area":null},{"id":"2310.16397","title":"Learning Efficient Surrogate Dynamic Models with Graph Spline Networks","created":"2023-10-25","cited_by_count":2,"area":null},{"id":"2410.01655","title":"Reevaluating Meta-Learning Optimization Algorithms Through Contextual Self-Modulation","created":"2024-10-02","cited_by_count":2,"area":null},{"id":"2501.16325","title":"Tailored Forecasting from Short Time Series via Meta-learning","created":"2025-01-27","cited_by_count":2,"area":null},{"id":"2508.11205","title":"Meta-learning Structure-Preserving Dynamics","created":"2025-08-15","cited_by_count":2,"area":null},{"id":"2509.24332","title":"Towards Generalizable PDE Dynamics Forecasting via Physics-Guided Invariant Learning","created":"2025-09-29","cited_by_count":2,"area":null},{"id":"2510.19784","title":"Environment Inference for Learning Generalizable Dynamical System","created":"2025-10-22","cited_by_count":2,"area":null},{"id":"2511.05456","title":"Parameter-Efficient Conditioning for Material Generalization in Graph-Based Simulators","created":"2025-11-07","cited_by_count":2,"area":null},{"id":"2605.25353","title":"PDEInvBench: A Comprehensive Dataset and Design Space Exploration of Neural Networks for PDE Inverse Problems","created":"2026-05-25","cited_by_count":2,"area":null},{"id":"2610.01974","title":"Sim+Real: Joint Simulation-Experiment Training Improves Balanced Prediction in Physical Systems","created":"2026-10-01","cited_by_count":1,"area":null},{"id":"2403.08194","title":"Unsupervised Learning of Hybrid Latent Dynamics: A Learn-to-Identify Framework","created":"2024-03-13","cited_by_count":0,"area":null},{"id":"2410.01476","title":"Reducing Variance in Meta-Learning via Laplace Approximation for Regression Tasks","created":"2024-10-02","cited_by_count":0,"area":null},{"id":"2506.19609","title":"Beyond Static Models: Hypernetworks for Adaptive and Generalizable Forecasting in Complex Parametric Dynamical Systems","created":"2025-06-24","cited_by_count":0,"area":null},{"id":"2507.00025","title":"Generalizing to New Dynamical Systems via Frequency Domain Adaptation","created":"2025-06-17","cited_by_count":0,"area":null},{"id":"2510.24216","title":"Unlocking Out-of-Distribution Generalization in Dynamics through Physics-Guided Augmentation","created":"2025-10-28","cited_by_count":0,"area":null},{"id":"2601.17465","title":"Bayesian quantum sensing using graybox machine learning","created":"2026-01-24","cited_by_count":0,"area":null},{"id":"2602.22630","title":"HyperKKL: Enabling Non-Autonomous State Estimation through Dynamic Weight Conditioning","created":"2026-02-26","cited_by_count":0,"area":null},{"id":"2603.10489","title":"JEDI: Jointly Embedded Inference of Neural Dynamics","created":"2026-03-11","cited_by_count":0,"area":null},{"id":"2603.22655","title":"Generalizing Dynamics Modeling More Easily from Representation Perspective","created":"2026-03-24","cited_by_count":0,"area":null},{"id":"2605.13088","title":"Bayesian Nonparametric Mixed-Effect ODEs with Gaussian Processes","created":"2026-05-13","cited_by_count":0,"area":null},{"id":"2605.23470","title":"Learning Individual Dynamics from Sparse Cross-Sectional Snapshots","created":"2026-05-22","cited_by_count":0,"area":null},{"id":"2605.30592","title":"Learning Transferable Predictability Representations","created":"2026-05-28","cited_by_count":0,"area":null},{"id":"2606.22969","title":"Topological Out-of-Domain Generalization in Dynamical Systems Reconstruction","created":"2026-06-22","cited_by_count":0,"area":null},{"id":"2607.14937","title":"A Minimal Interpretable Architecture for Zero-Shot Reconstruction of Dynamical Systems","created":"2026-07-16","cited_by_count":0,"area":null},{"id":"2610.10398","title":"Cross-Domain Pretraining for Steady-State Neural CFD Surrogates","created":"2026-10-07","cited_by_count":0,"area":null},{"id":"2610.17029","title":"SPLICE: Sparse Physics Library Identification and Compositional Expansion","created":"2026-10-12","cited_by_count":0,"area":null}],"next_cursor":null}