% Key papers for Switching and law-discovery dynamics (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{icml2018_graph_36727,
  title = {{Graph Networks as Learnable Physics Engines for Inference and Control}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2220},
}

@inproceedings{icml2018_neural_36871,
  title = {{Neural Relational Inference for Interacting Systems}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2083},
}

@inproceedings{iclr2020_symplectic_29343,
  title = {{Symplectic Recurrent Neural Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=BkgYPREtPr},
}

@inproceedings{icml2018_comparing_36578,
  title = {{Comparing Dynamics: Deep Neural Networks versus Glassy Systems}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2190},
}

@inproceedings{neurips2020_recurrent_60679,
  title = {{Recurrent Switching Dynamical Systems Models for Multiple Interacting Neural Populations}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/19016},
}

@inproceedings{iclr2019_tree_28954,
  title = {{Tree-Structured Recurrent Switching Linear Dynamical Systems for Multi-Scale Modeling}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/888},
}

@inproceedings{iclr2022_ilqr_31822,
  title = {{iLQR-VAE : control-based learning of input-driven dynamics with applications to neural data}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6079},
}

@inproceedings{icml2018_robust_36965,
  title = {{Robust and Scalable Models of Microbiome Dynamics}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2382},
}

@inproceedings{aaai2018_reduced_102399,
  title = {{Reduced-Rank Linear Dynamical Systems}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11666},
}

@inproceedings{icml2020_causal_38004,
  title = {{Causal Modeling for Fairness In Dynamical Systems}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6548},
}

@inproceedings{aaai2016_understanding_105445,
  title = {{Understanding City Traffic Dynamics Utilizing Sensor and Textual Observations}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2016},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/9902},
}

@inproceedings{aaai2020_dynamical_102279,
  title = {{Dynamical System Inspired Adaptive Time Stepping Controller for Residual Network Families}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/6141},
}

@inproceedings{iclr2020_intrinsically_29832,
  title = {{Intrinsically Motivated Discovery of Diverse Patterns in Self-Organizing Systems}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=rkg6sJHYDr},
}

@inproceedings{aaai2020_true_99742,
  title = {{True Nonlinear Dynamics from Incomplete Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5343},
}

@inproceedings{aaai2016_automated_104940,
  title = {{Automated Verification and Tightening of Failure Propagation Models}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2016},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10094},
}

@inproceedings{aaai2021_learning_870,
  title = {{Learning Dynamics Models with Stable Invariant Sets}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/09782-learning-dynamics-models-with-stable-invariant-sets/},
}

@inproceedings{icml2023_geometric_41834,
  title = {{Geometric Clifford Algebra Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/24098},
}

@inproceedings{neurips2021_neural_62139,
  title = {{Neural Hybrid Automata: Learning Dynamics With Multiple Modes and Stochastic Transitions}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27230},
}

@inproceedings{neurips2021_reverse_63170,
  title = {{Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/28358},
}

@inproceedings{icml2022_tractable_41280,
  title = {{Tractable Dendritic RNNs for Reconstructing Nonlinear Dynamical Systems}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/17351},
}

@inproceedings{neurips2024_modeling_71696,
  title = {{Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95587},
}

@inproceedings{aaai2025_learning_9728,
  title = {{Learning Deep Dissipative Dynamics}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34175},
}

@inproceedings{neurips2024_controlsynth_73069,
  title = {{ControlSynth Neural ODEs: Modeling Dynamical Systems with Guaranteed Convergence}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94357},
}

@inproceedings{neurips2024_back_73262,
  title = {{Back to the Continuous Attractor}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94178},
}

@inproceedings{aaai2024_dynamic_5772,
  title = {{Dynamic Tangled Derivative Logic of Metric Spaces}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28920},
}

@inproceedings{aaai2024_exact_5888,
  title = {{Exact Inference for Continuous-Time Gaussian Process Dynamics}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29074},
}

@inproceedings{icml2024_out_45744,
  title = {{Out-of-Domain Generalization in Dynamical Systems Reconstruction}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/32708},
}

@inproceedings{iclr2025_braid_80717,
  title = {{BRAID: Input-driven Nonlinear Dynamical Modeling of Neural-Behavioral Data}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/31051},
}

@inproceedings{aaai2024_learning_6501,
  title = {{Learning the Topology and Behavior of Discrete Dynamical Systems}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29390},
}

@inproceedings{iclr2024_course_33799,
  title = {{Course Correcting Koopman Representations}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19276},
}

@inproceedings{icml2026_meta_53925,
  title = {{Meta-learning Structure-Preserving Dynamics}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=k66TZFhUSQ},
}

@inproceedings{neurips2024_noether_73113,
  title = {{Noether's Razor: Learning Conserved Quantities}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94316},
}

@inproceedings{neurips2024_almost_74141,
  title = {{Almost-Linear RNNs Yield Highly Interpretable Symbolic Codes in Dynamical Systems Reconstruction}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93399},
}

@inproceedings{neurips2025_characterizing_76315,
  title = {{Characterizing control between interacting subsystems with deep Jacobian estimation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=I822ZIRtms},
}

@inproceedings{neurips2025_lam_79091,
  title = {{LaM-SLidE: Latent Space Modeling of Spatial Dynamical Systems via Linked Entities}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=lTEjpeTXIo},
}

@inproceedings{icml2024_optimal_43993,
  title = {{Optimal Recurrent Network Topologies for Dynamical Systems Reconstruction}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34459},
}

@inproceedings{icml2024_amortized_45645,
  title = {{Amortized Equation Discovery in Hybrid Dynamical Systems}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/32807},
}

@inproceedings{icml2025_discovering_48230,
  title = {{Discovering Physics Laws of Dynamical Systems via Invariant Function Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44382},
}

@inproceedings{icml2026_equilibrium_49721,
  title = {{Equilibrium Propagation for Non-Conservative Systems}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=5785emCgS1},
}

@inproceedings{icml2026_adaptive_53173,
  title = {{Adaptive Symmetry Discovery for Dynamical System Identification}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=crYiAjVBo0},
}