% Key papers for Stochastic population dynamics (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{icml2020_trajectorynet_38883,
  title = {{TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6491},
}

@inproceedings{neurips2023_timewarp_67434,
  title = {{Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/72299},
}

@inproceedings{icml2022_variational_41336,
  title = {{Variational Mixtures of ODEs for Inferring Cellular Gene Expression Dynamics}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/16629},
}

@inproceedings{neurips2023_implicit_66619,
  title = {{Implicit Transfer Operator Learning: Multiple Time-Resolution Models for Molecular Dynamics}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/73001},
}

@inproceedings{neurips2025_consistent_78661,
  title = {{Consistent Sampling and Simulation: Molecular Dynamics with Energy-Based Diffusion Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=gzYuvZg28E},
}

@inproceedings{neurips2021_an_63206,
  title = {{An Extensible Benchmark Suite for Learning to Simulate Physical Systems}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://openreview.net/forum?id=pY9MHwmrymR},
}

@inproceedings{neurips2024_from_72301,
  title = {{From Biased to Unbiased Dynamics: An Infinitesimal Generator Approach}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95044},
}

@inproceedings{neurips2025_modeling_77918,
  title = {{Modeling Cell Dynamics and Interactions with Unbalanced Mean Field Schrödinger Bridge}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=Z6DJJIN8IJ},
}

@inproceedings{neurips2025_flashmd_79379,
  title = {{FlashMD: long-stride, universal prediction of molecular dynamics}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=ogZu06NgQs},
}

@inproceedings{iclr2025_boltzmann_83518,
  title = {{Boltzmann priors for Implicit Transfer Operators}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28298},
}

@inproceedings{iclr2023_neural_32890,
  title = {{Neural Lagrangian Schr"odinger Bridge: Diffusion Modeling for Population Dynamics}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11558},
}

@inproceedings{icml2023_action_41860,
  title = {{Action Matching: Learning Stochastic Dynamics from Samples}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/23493},
}

@inproceedings{icml2025_deep_46034,
  title = {{Deep Neural Cellular Potts Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46513},
}

@inproceedings{icml2025_universal_48971,
  title = {{Universal Approximation of Mean-Field Models via Transformers}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43652},
}

@inproceedings{icml2026_constrained_52292,
  title = {{Constrained hybrid modelling to predict microbial dynamics and organic matter turnover in soil systems}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=UR1yz4AMYj},
}

@inproceedings{neurips2023_deep_70038,
  title = {{Deep Momentum Multi-Marginal Schrödinger Bridge}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/69934},
}

@inproceedings{neurips2024_foundation_73204,
  title = {{Foundation Inference Models for Markov Jump Processes}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94231},
}

@inproceedings{neurips2025_position_76302,
  title = {{Position: Biology is the Challenge Physics-Informed ML Needs to Evolve}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=HzGZVYi8fK},
}

@inproceedings{neurips2025_dynamic_79145,
  title = {{Dynamic Diffusion Schrödinger Bridge in Astrophysical Observational Inversions}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=mBgGg30LZu},
}

@inproceedings{iclr2025_meta_81078,
  title = {{Meta Flow Matching: Integrating Vector Fields on the Wasserstein Manifold}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30690},
}

@inproceedings{aaai2026_cellstream_99920,
  title = {{CellStream: Dynamical Optimal Transport Informed Embeddings for Reconstructing Cellular Trajectories from Snapshots Data}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/37041},
}

@inproceedings{icml2025_unisim_47556,
  title = {{UniSim: A Unified Simulator for Time-Coarsened Dynamics of Biomolecules}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45040},
}

@inproceedings{icml2026_two_49418,
  title = {{Two-Parameter Flows for Learning Population Dynamics of Physical Systems}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=2Opz9uBYQT},
}

@inproceedings{icml2026_learning_50619,
  title = {{Learning Hamiltonian Flow Maps: Mean Flow Consistency for Large-Timestep Molecular Dynamics}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=EBSn23DLwB},
}

@inproceedings{icml2026_leveraging_50661,
  title = {{Leveraging Gauge Freedom for Learning Non-Gradient Population Dynamics of Stochastic Systems}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=EZL7l4U2kk},
}

@inproceedings{icml2026_speculative_51011,
  title = {{Speculative Sampling For Faster Molecular Dynamics}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=I3SK0WFmD0},
}

@inproceedings{icml2026_beyond_51022,
  title = {{Beyond Continuity: Simulation-free Reconstruction of Discrete Branching Dynamics from Single-cell Snapshots}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=IABjbJlinz},
}

@inproceedings{icml2026_a_51478,
  title = {{A Call to Lagrangian Action: Learning Population Mechanics from Temporal Snapshots}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=MjPv4kRu3H},
}