{"total":57,"rows":[{"id":"2402.18377","title":"Out-of-Domain Generalization in Dynamical Systems Reconstruction","created":"2024-02-28","cited_by_count":33,"area":null},{"id":"2405.13888","title":"Marrying Causal Representation Learning with Dynamical Systems for Science","created":"2024-05-22","cited_by_count":23,"area":null},{"id":"2405.07761","title":"LLM4ED: Large Language Models for Automatic Equation Discovery","created":"2024-05-13","cited_by_count":14,"area":null},{"id":"2402.07594","title":"Zero-shot Imputation with Foundation Inference Models for Dynamical Systems","created":"2024-02-12","cited_by_count":13,"area":null},{"id":"2505.13755","title":"Panda: A pretrained forecast model for chaotic dynamics","created":"2025-05-19","cited_by_count":13,"area":null},{"id":"2605.24043","title":"LLM-AutoSciLab: Closed-Loop Scientific Discovery via Active Experimentation with LLMs","created":"2026-05-21","cited_by_count":12,"area":null},{"id":"2509.24762","title":"In-Context Learning of Temporal Point Processes with Foundation Inference Models","created":"2025-09-29","cited_by_count":10,"area":null},{"id":"2409.15167","title":"Data-driven model discovery with Kolmogorov-Arnold networks","created":"2024-09-23","cited_by_count":9,"area":null},{"id":"2410.14673","title":"Self-supervised contrastive learning performs non-linear system identification","created":"2024-10-18","cited_by_count":9,"area":null},{"id":"2502.19049","title":"In-Context Learning of Stochastic Differential Equations with Foundation Inference Models","created":"2025-02-26","cited_by_count":7,"area":null},{"id":"2506.09816","title":"Identifiability Challenges in Sparse Linear Ordinary Differential Equations","created":"2025-06-11","cited_by_count":7,"area":null},{"id":"2509.20529","title":"MDBench: Benchmarking Data-Driven Methods for Model Discovery","created":"2025-09-24","cited_by_count":7,"area":null},{"id":"2504.02630","title":"Grammar-based Ordinary Differential Equation Discovery","created":"2025-04-03","cited_by_count":6,"area":null},{"id":"2406.03585","title":"A Comparison of Recent Algorithms for Symbolic Regression to Genetic Programming","created":"2024-06-05","cited_by_count":5,"area":null},{"id":"2410.06074","title":"Scalable Mechanistic Neural Networks for Differential Equations and Machine Learning","created":"2024-10-08","cited_by_count":5,"area":null},{"id":"2501.11350","title":"Adaptive parameters identification for nonlinear dynamics using deep permutation invariant networks","created":"2025-01-20","cited_by_count":5,"area":null},{"id":"2502.01702","title":"Al-Khwarizmi: Discovering Physical Laws with Foundation Models","created":"2025-02-03","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":"2502.18377","title":"Mechanistic PDE Networks for Discovery of Governing Equations","created":"2025-02-25","cited_by_count":4,"area":null},{"id":"2510.25368","title":"Position: Biology is the Challenge Physics-Informed ML Needs to Evolve","created":"2025-10-29","cited_by_count":4,"area":null},{"id":"2603.20910","title":"LLM-ODE: Data-driven Discovery of Dynamical Systems with Large Language Models","created":"2026-03-21","cited_by_count":4,"area":null},{"id":"2409.01416","title":"Active Symbolic Discovery of Ordinary Differential Equations via Phase Portrait Sketching","created":"2024-09-02","cited_by_count":3,"area":null},{"id":"2512.10282","title":"Neuronal Attention Circuit (NAC) for Representation Learning","created":"2025-12-11","cited_by_count":3,"area":null},{"id":"2602.08733","title":"Foundation Inference Models for Ordinary Differential Equations","created":"2026-02-09","cited_by_count":3,"area":null},{"id":"2606.09638","title":"Data-driven discovery of governing differential equations across physical systems","created":"2026-06-08","cited_by_count":3,"area":null},{"id":"2410.11185","title":"Neural Symbolic Regression of Complex Network Dynamics","created":"2024-10-15","cited_by_count":2,"area":null},{"id":"2508.21484","title":"Data-driven Discovery of Digital Twins in Biomedical Research","created":"2025-08-29","cited_by_count":2,"area":null},{"id":"2509.10089","title":"KAN-SR: A Kolmogorov-Arnold Network Guided Symbolic Regression Framework","created":"2025-09-12","cited_by_count":2,"area":null},{"id":"2510.23295","title":"Predicting symbolic ODEs from multiple trajectories","created":"2025-10-27","cited_by_count":2,"area":null},{"id":"2511.00102","title":"Automated Discovery of Conservation Laws via Hybrid Neural ODE-Transformers","created":"2025-10-30","cited_by_count":2,"area":null},{"id":"2602.08885","title":"Breaking the Simplification Bottleneck in Amortized Neural Symbolic Regression","created":"2026-02-09","cited_by_count":2,"area":null},{"id":"2604.16232","title":"Neuro-Symbolic ODE Discovery with Latent Grammar Flow","created":"2026-04-17","cited_by_count":2,"area":null},{"id":"2605.09696","title":"Discovery of Nonlinear Dynamics with Automated Basis Function Generation","created":"2026-05-10","cited_by_count":2,"area":null},{"id":"2606.13260","title":"Extracting Governing Equations from Latent Dynamics via Multi-View Contrastive Learning","created":"2026-06-11","cited_by_count":2,"area":null},{"id":"2507.07808","title":"Bridging Logic and Learning: Decoding Temporal Logic Embeddings via Transformers","created":"2025-07-10","cited_by_count":1,"area":null},{"id":"2508.06383","title":"Tree-Based Deep Learning for Ranking Symbolic Integration Algorithms","created":"2025-08-08","cited_by_count":1,"area":null},{"id":"2510.02903","title":"Learning Explicit Single-Cell Dynamics Using ODE Representations","created":"2025-10-03","cited_by_count":1,"area":null},{"id":"2510.12618","title":"Towards Fast Coarse-graining and Equation Discovery with Foundation Inference Models","created":"2025-10-14","cited_by_count":1,"area":null},{"id":"2605.04421","title":"FLUID: Continuous-Time Hyperconnected Sparse Transformer for Sink-Free Learning","created":"2026-05-06","cited_by_count":1,"area":null},{"id":"2605.21813","title":"Symbolic Density Estimation for Discrete Distributions","created":"2026-05-20","cited_by_count":1,"area":null},{"id":"2607.18490","title":"The Dynamics of Discoverability: How Trajectories and Priors Shape Equation Recovery","created":"2026-07-20","cited_by_count":1,"area":null},{"id":"2607.23337","title":"Neural operator discovery from heterogeneous trajectories","created":"2026-07-25","cited_by_count":1,"area":null},{"id":"2311.13247","title":"A projected nonlinear state-space model for forecasting time series signals","created":"2023-11-22","cited_by_count":0,"area":null},{"id":"2506.18522","title":"DDOT: A Derivative-directed Dual-decoder Ordinary Differential Equation Transformer for Dynamic System Modeling","created":"2025-06-23","cited_by_count":0,"area":null},{"id":"2510.12650","title":"Towards Foundation Inference Models that Learn ODEs In-Context","created":"2025-10-14","cited_by_count":0,"area":null},{"id":"2601.22328","title":"Knowledge-Informed Kernel State Reconstruction from Heterogeneous Partial Observations","created":"2026-01-29","cited_by_count":0,"area":null},{"id":"2604.06081","title":"A machine learning framework for uncovering stochastic nonlinear dynamics from noisy data","created":"2026-04-07","cited_by_count":0,"area":null},{"id":"2605.07323","title":"Discovering Ordinary Differential Equations with LLM-Based Qualitative and Quantitative Evaluation","created":"2026-05-08","cited_by_count":0,"area":null},{"id":"2606.19145","title":"OrthoReg: Orthogonal Regularization for Hybrid Symbolic-Neural Dynamical Systems","created":"2026-06-17","cited_by_count":0,"area":null},{"id":"2608.02662","title":"Verifier-Guided Model Discovery for Physical Dynamical Systems with Pretrained Symbolic Transformers","created":"2026-08-01","cited_by_count":0,"area":null},{"id":"2608.22112","title":"Symbolic Neural ODEs: Learning interpretable models from time-series data","created":"2026-08-22","cited_by_count":0,"area":null},{"id":"2608.27475","title":"Hypothesize, Evaluate, Refine: A Scientific Agent for PDE Discovery with Unknown Spatial Coefficient Fields","created":"2026-08-19","cited_by_count":0,"area":null},{"id":"2609.05207","title":"FluxDisco: Symbolic Regression for Stoichiometric Dynamical Systems via Monte Carlo Graph Search","created":"2026-09-04","cited_by_count":0,"area":null},{"id":"2609.16710","title":"Continuous-Time Machine Learning: A Unified Mathematical Perspective","created":"2026-09-15","cited_by_count":0,"area":null},{"id":"2609.37083","title":"Identifying ODEs from Unstructured Data with Causal Representation Learning","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2610.03947","title":"Synthesizing Physics Formulae with Transformers","created":"2026-10-02","cited_by_count":0,"area":null},{"id":"2610.16812","title":"DASS: A Solver-Adaptable Dynamic Auxiliary Search Strategy for Symbolic Regression","created":"2026-10-12","cited_by_count":0,"area":null}],"next_cursor":null}