@inproceedings{kim2026inverting,
  title = {Inverting Data Transformations via Diffusion Sampling},
  author = {Kim, Jinwoo and Kaba, S{\'e}kou-Oumar and Park, Jiyun and Hong, Seunghoon and Ravanbakhsh, Siamak},
  booktitle = {Forty-third International Conference on Machine Learning},
  year = {2026}
}

@inproceedings{pedramfarmulti,
  title = {Multi-Armed Sampling Problem and the End of Exploration},
  author = {Pedramfar, Mohammad and Ravanbakhsh, Siamak},
  booktitle = {The 29th International Conference on Artificial Intelligence and Statistics},
  year = {2026},
  organization = {PMLR},
  url_arxiv = {https://arxiv.org/abs/2507.10797}
}

@inproceedings{ngo2025scaling,
  title = {Scaling laws and symmetry, evidence from neural force fields},
  author = {Ngo, Khang and Ravanbakhsh, Siamak},
  booktitle = {The Fourteenth International Conference on Learning Representations},
  year = {2026},
  url_arxiv = {https://arxiv.org/abs/2510.09768}
}

@article{jain2026diffusion,
  title = {Diffusion Tree Sampling: Scalable inference-time alignment of diffusion models},
  author = {Jain, Vineet and Sareen, Kusha and Pedramfar, Mohammad and Ravanbakhsh, Siamak},
  journal = {Advances in Neural Information Processing Systems},
  volume = {38},
  pages = {145576--145615},
  year = {2025},
  url_paper = {https://proceedings.neurips.cc/paper_files/paper/2025/file/d6484394c4cb5e1f4ecad8d90b912025-Paper-Conference.pdf}
}

@article{kaba2026energy,
  title = {Energy Loss Functions for Physical Systems},
  author = {Kaba, Oumar and Sareen, Kusha and Levy, Daniel and Ravanbakhsh, Siamak},
  journal = {Advances in Neural Information Processing Systems},
  volume = {38},
  pages = {163916--163947},
  year = {2025},
  url_paper = {https://proceedings.neurips.cc/paper_files/paper/2025/file/efd3901eeda94e200f0634f3a27298b8-Paper-Conference.pdf}
}

@article{li2025identifiability,
  title = {On the Identifiability of Causal Abstractions},
  author = {Li, Xiusi and Kaba, S{\'e}kou-Oumar and Ravanbakhsh, Siamak},
  journal = {The 28th International Conference on Artificial Intelligence and Statistics},
  year = {2025},
  organization = {PMLR},
  url_arxiv = {https://arxiv.org/abs/2503.10834},
  url_paper = {https://openreview.net/attachment?id=RKiOGRrABL&name=pdf}
}

@inproceedings{levysymmcd,
  title = {SymmCD: Symmetry-Preserving Crystal Generation with Diffusion Models},
  author = {Levy, Daniel and Panigrahi, Siba Smarak and Kaba, S{\'e}kou-Oumar and Zhu, Qiang and Lee, Kin Long Kelvin and Galkin, Mikhail and Miret, Santiago and Ravanbakhsh, Siamak},
  booktitle = {The Thirteenth International Conference on Learning Representations},
  year = {2025},
  url_paper = {https://openreview.net/pdf?id=xnssGv9rpW},
  url_arxiv = {https://arxiv.org/abs/2502.03638}
}

@inproceedings{mondalefficient,
  title = {Efficient Dynamics Modeling in Interactive Environments with Koopman Theory},
  author = {Mondal, Arnab Kumar and Panigrahi, Siba Smarak and Rajeswar, Sai and Siddiqi, Kaleem and Ravanbakhsh, Siamak},
  booktitle = {The Twelfth International Conference on Learning Representations},
  year = {2024},
  url_arxiv = {https://arxiv.org/abs/2306.11941},
  url_paper = {https://openreview.net/pdf?id=fkrYDQaHOJ}
}

@inproceedings{jainlearning,
  title = {Learning to Reach Goals via Diffusion},
  author = {Jain, Vineet and Ravanbakhsh, Siamak},
  booktitle = {Forty-first International Conference on Machine Learning},
  year = {2024},
  url_paper = {https://openreview.net/pdf?id=3JhmHCVPa8},
  url_arxiv = {https://arxiv.org/abs/2310.02505}
}

@inproceedings{livernochediffusion,
  title = {On Diffusion Modeling for Anomaly Detection},
  author = {Livernoche, Victor and Jain, Vineet and Hezaveh, Yashar and Ravanbakhsh, Siamak},
  booktitle = {The Twelfth International Conference on Learning Representations},
  year = {2024},
  url_paper = {https://openreview.net/pdf?id=lR3rk7ysXz},
  url_arxiv = {https://arxiv.org/abs/2305.18593}
}

@inproceedings{pmlr-v202-kaba23a,
  title = {Equivariance with Learned Canonicalization Functions},
  author = {Kaba, S\'{e}kou-Oumar and Mondal, Arnab Kumar and Zhang, Yan and Bengio, Yoshua and Ravanbakhsh, Siamak},
  booktitle = {Proceedings of the 40th International Conference on Machine Learning},
  pages = {15546--15566},
  year = {2023},
  editor = {Krause, Andreas and Brunskill, Emma and Cho, Kyunghyun and Engelhardt, Barbara and Sabato, Sivan and Scarlett, Jonathan},
  volume = {202},
  series = {Proceedings of Machine Learning Research},
  month = {23--29 Jul},
  publisher = {PMLR},
  url_pdf = {https://proceedings.mlr.press/v202/kaba23a/kaba23a.pdf},
  url = {https://proceedings.mlr.press/v202/kaba23a.html}
}

@inproceedings{mondal2023equivariant,
  title = {Equivariant Adaptation of Large Pretrained Models},
  author = {Mondal, Arnab Kumar and Panigrahi, Siba Smarak and Kaba, S{\'e}kou-Oumar and Rajeswar, Sai and Ravanbakhsh, Siamak},
  booktitle = {Thirty-seventh Conference on Neural Information Processing Systems},
  year = {2023},
  url_pdf = {https://arxiv.org/abs/2310.01647}
}

@inproceedings{akhound2023lieneurips,
  title = {Lie Point Symmetry and Physics Informed Networks},
  author = {Akhound-Sadegh, Tara and Perreault-Levasseur, Laurence and Brandstetter, Johannes and Welling, Max and Ravanbakhsh, Siamak},
  booktitle = {Thirty-seventh Conference on Neural Information Processing Systems},
  year = {2023},
  url_pdf = {https://arxiv.org/abs/2311.04293}
}

@inproceedings{mondal2022eqr,
  title = {EqR: Equivariant Representations for Data-Efficient Reinforcement Learning},
  author = {Mondal, Arnab Kumar and Jain, Vineet and Siddiqi, Kaleem and Ravanbakhsh, Siamak},
  booktitle = {International Conference on Machine Learning},
  pages = {15908--15926},
  year = {2022},
  organization = {PMLR},
  url_pdf = {https://proceedings.mlr.press/v162/mondal22a/mondal22a.pdf},
  url_code = {https://github.com/arnab39/Symmetry-RL}
}

@inproceedings{NEURIPS2022_1abed6ee,
  author = {Kaba, Oumar and Ravanbakhsh, Siamak},
  booktitle = {Advances in Neural Information Processing Systems},
  editor = {S. Koyejo and S. Mohamed and A. Agarwal and D. Belgrave and K. Cho and A. Oh},
  pages = {4150--4164},
  publisher = {Curran Associates, Inc.},
  title = {Equivariant Networks for Crystal Structures},
  url_pdf = {https://proceedings.neurips.cc/paper_files/paper/2022/file/1abed6ee581b9ceb4e2ddf37822c7fcb-Paper-Conference.pdf},
  volume = {35},
  year = {2022}
}

@inproceedings{pmlr-v162-morris22a,
  title = {{S}peq{N}ets: Sparsity-aware permutation-equivariant graph networks},
  author = {Morris, Christopher and Rattan, Gaurav and Kiefer, Sandra and Ravanbakhsh, Siamak},
  booktitle = {Proceedings of the 39th International Conference on Machine Learning},
  pages = {16017--16042},
  year = {2022},
  editor = {Chaudhuri, Kamalika and Jegelka, Stefanie and Song, Le and Szepesvari, Csaba and Niu, Gang and Sabato, Sivan},
  volume = {162},
  series = {Proceedings of Machine Learning Research},
  month = {17--23 Jul},
  publisher = {PMLR},
  url_pdf = {https://proceedings.mlr.press/v162/morris22a/morris22a.pdf}
}

@inproceedings{NEURIPS2022_dcd29769,
  author = {Shakerinava, Mehran and Mondal, Arnab Kumar and Ravanbakhsh, Siamak},
  booktitle = {Advances in Neural Information Processing Systems},
  editor = {S. Koyejo and S. Mohamed and A. Agarwal and D. Belgrave and K. Cho and A. Oh},
  pages = {34162--34174},
  publisher = {Curran Associates, Inc.},
  title = {Structuring Representations Using Group Invariants},
  url_pdf = {https://proceedings.neurips.cc/paper_files/paper/2022/file/dcd297696d0bb304ba426b3c5a679c37-Paper-Conference.pdf},
  volume = {35},
  year = {2022}
}

@inproceedings{shakerinava2022utility,
  title = {Utility Theory for Sequential Decision Making},
  author = {Shakerinava, Mehran and Ravanbakhsh, Siamak},
  booktitle = {International Conference on Machine Learning},
  pages = {19616--19625},
  year = {2022},
  organization = {PMLR},
  url_pdf = {https://proceedings.mlr.press/v162/shakerinava22a/shakerinava22a.pdf}
}

@inproceedings{pmlr-v139-shakerinava21a,
  title = {Equivariant Networks for Pixelized Spheres},
  author = {Shakerinava, Mehran and Ravanbakhsh, Siamak},
  booktitle = {Proceedings of the 38th International Conference on Machine Learning},
  pages = {9477--9488},
  year = {2021},
  editor = {Meila, Marina and Zhang, Tong},
  volume = {139},
  series = {Proceedings of Machine Learning Research},
  month = {18--24 Jul},
  publisher = {PMLR},
  url_pdf = {http://proceedings.mlr.press/v139/shakerinava21a/shakerinava21a.pdf},
  url_code = {https://github.com/mshakerinava/Equivariant-Networks-for-Pixelized-Spheres}
}

@article{graham2020deep,
  title = {Equivariant Entity-Relationship Networks},
  author = {Graham, Devon and Wang, Junhao and Ravanbakhsh, Siamak},
  journal = {arXiv preprint arXiv:1903.09033},
  url_arxiv = {https://arxiv.org/abs/1903.09033},
  url_code = {https://github.com/drgrhm/exch_model},
  year = {2020}
}

@inproceedings{wang2020equivariant,
  author = {Wang, Renhao and Albooyeh, Marjan and Ravanbakhsh, Siamak},
  booktitle = {Advances in Neural Information Processing Systems},
  editor = {H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin},
  pages = {13806--13817},
  publisher = {Curran Associates, Inc.},
  title = {Equivariant Networks for Hierarchical Structures},
  url_pdf = {https://proceedings.neurips.cc/paper/2020/file/9efb1a59d7b58e69996cf0e32cb71098-Paper.pdf},
  url_arxiv = {http://proceedings.mlr.press/v119/ravanbakhsh20a/ravanbakhsh20a.pdf},
  url_code = {https://github.com/rw435/wreathProdNet},
  volume = {33},
  year = {2020}
}

@inproceedings{pmlr-v119-ravanbakhsh20a,
  title = {Universal Equivariant Multilayer Perceptrons},
  author = {Ravanbakhsh, Siamak},
  booktitle = {Proceedings of the 37th International Conference on Machine Learning},
  pages = {7996--8006},
  year = {2020},
  editor = {Hal Daumé III and Aarti Singh},
  volume = {119},
  series = {Proceedings of Machine Learning Research},
  address = {Virtual},
  month = {13--18 Jul},
  publisher = {PMLR},
  url_pdf = {http://proceedings.mlr.press/v119/ravanbakhsh20a/ravanbakhsh20a.pdf}
}

@inproceedings{pmlr-v80-hartford18a,
  title = {Deep Models of Interactions Across Sets},
  author = {Hartford, Jason and Graham, Devon and Leyton-Brown, Kevin and Ravanbakhsh, Siamak},
  booktitle = {Proceedings of the 35th International Conference on Machine Learning},
  pages = {1909--1918},
  year = {2018},
  volume = {80},
  series = {PMLR},
  month = {Jul},
  publisher = {PMLR},
  url_pdf = {http://proceedings.mlr.press/v80/hartford18a/hartford18a-supp.pdf},
  url_arxiv = {https://arxiv.org/abs/1803.02879}
}

@inproceedings{NIPS2017_6931,
  title = {Deep Sets},
  author = {Zaheer, Manzil and Kottur, Satwik and Ravanbakhsh, Siamak and Poczos, Barnabas and Salakhutdinov, Ruslan R and Smola, Alexander J},
  booktitle = {Advances in Neural Information Processing Systems 30},
  pages = {3391--3401},
  year = {2017},
  publisher = {Curran Associates, Inc.},
  url_pdf = {http://papers.nips.cc/paper/6931-deep-sets.pdf},
  url_arxiv = {https://arxiv.org/abs/1703.06114},
  url_code = {https://github.com/manzilzaheer/DeepSets}
}

@inproceedings{ravanbakhsh_equivariance,
  author = {Ravanbakhsh, Siamak and Schneider, Jeff and Poczos, Barnabas},
  title = {Equivariance Through Parameter-Sharing},
  booktitle = {Proceedings of International Conference on Machine Learning},
  series = {JMLR: W&CP},
  volume = {70},
  year = {2017},
  month = {August},
  url_arxiv = {https://arxiv.org/abs/1702.08389},
  url_pdf = {http://proceedings.mlr.press/v70/ravanbakhsh17a/ravanbakhsh17a-supp.pdf}
}

@inproceedings{ravanbakhsh_boolean,
  title = {Boolean Matrix Factorization and Noisy Completion via Message Passing},
  author = {Ravanbakhsh, Siamak and P{\'o}czos, Barnab{\'a}s and Greiner, Russell},
  booktitle = {Proceedings of The 33rd International Conference on Machine Learning},
  series = {JMLR: W&CP},
  volume = {48},
  year = {2016},
  url_pdf = {http://jmlr.org/proceedings/papers/v48/ravanbakhsha16.pdf},
  url_code = {https://github.com/mravanba/BooleanFactorization}
}

@inproceedings{ravanbakhsh_exprbm,
  author = {Ravanbakhsh, Siamak and Poczos, Barnabas and Schneider, Jeff and Schuurmans, Dale and Greiner, Russell},
  title = {Stochastic Neural Networks with Monotonic Activation Functions},
  booktitle = {International Conference on Artificial Intelligence and Statistics},
  series = {JMLR: W&CP},
  volume = {51},
  pages = {809–818},
  year = {2016},
  url_pdf = {http://www.jmlr.org/proceedings/papers/v51/ravanbakhsh16.pdf}
}