{"total":14,"rows":[{"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":"2410.14240","title":"Almost-Linear RNNs Yield Highly Interpretable Symbolic Codes in Dynamical Systems Reconstruction","created":"2024-10-18","cited_by_count":19,"area":null},{"id":"2406.16749","title":"Inferring stochastic low-rank recurrent neural networks from neural data","created":"2024-06-24","cited_by_count":15,"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":"2403.12636","title":"A Practical Guide to Sample-based Statistical Distances for Evaluating Generative Models in Science","created":"2024-03-19","cited_by_count":14,"area":null},{"id":"2506.07919","title":"Uncovering the Computational Roles of Nonlinearity in Sequence Modeling Using Almost-Linear RNNs","created":"2025-06-09","cited_by_count":5,"area":null},{"id":"2602.15649","title":"Continuous-Time Piecewise-Linear Recurrent Neural Networks","created":"2026-02-17","cited_by_count":4,"area":null},{"id":"2602.16864","title":"Position: A Dynamical Systems Perspective is Needed to Advance Time Series Modeling","created":"2026-02-18","cited_by_count":4,"area":null},{"id":"2510.03814","title":"Detecting Invariant Manifolds in ReLU-Based RNNs","created":"2025-10-04","cited_by_count":3,"area":null},{"id":"2510.01089","title":"Double projection for reconstructing dynamical systems: between stochastic and deterministic regimes","created":"2025-10-01","cited_by_count":1,"area":null},{"id":"2605.31547","title":"The Dynamic-Probabilistic Consistency Gap in Chaotic Surrogate Modeling","created":"2026-05-29","cited_by_count":1,"area":null},{"id":"2507.02103","title":"What Neuroscience Can Teach AI About Learning in Continuously Changing Environments","created":"2025-07-02","cited_by_count":0,"area":null},{"id":"2605.12683","title":"Parallel-in-Time Training of Recurrent Neural Networks for Dynamical Systems Reconstruction","created":"2026-05-12","cited_by_count":0,"area":null},{"id":"2610.03065","title":"Learning Transferable Policies from Action-free Time Series Through Dynamical Embeddings","created":"2026-10-02","cited_by_count":0,"area":null}],"next_cursor":null}