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@article{albergo2025stochasticinterpolants,
  author = {Michael Albergo and Nicholas M. Boffi and Eric Vanden-Eijnden},
  title = {{Stochastic Interpolants: A Unifying Framework for Flows and Diffusions}},
  journal = {Journal of Machine Learning Research},
  year = {2025},
  volume = {26},
  number = {209},
  pages = {1--80},
  url = {http://jmlr.org/papers/v26/23-1605.html}
}

@inproceedings{austin2021d3pm,
  title = {{Structured Denoising Diffusion Models in Discrete State-Spaces}},
  author = {Austin, Jacob and Johnson, Daniel D. and Ho, Jonathan and Tarlow, Daniel and van den Berg, Rianne},
  year = {2021},
  booktitle = {Advances in Neural Information Processing Systems},
  volume = {34},
  url = {https://proceedings.neurips.cc/paper_files/paper/2021/hash/958c530554f78bcd8e97125b70e6973d-Abstract.html},
  pages = {17981--17993}
}

@inproceedings{backward,
  title = {{Optimizing Backward Policies in GFlowNets via Trajectory Likelihood Maximization}},
  author = {Gritsaev, Timofei and Morozov, Nikita and Samsonov, Sergey and Tiapkin, Daniil},
  year = {2025},
  booktitle = {International Conference on Learning Representations},
  url = {https://proceedings.iclr.cc/paper_files/paper/2025/hash/f3efbcfe76bed022a37c5aeb1daf2326-Abstract-Conference.html},
  pages = {98281--98301}
}

@article{boffi2025flowmapmatching,
  title = {{Flow map matching with stochastic interpolants: A mathematical framework for consistency models}},
  author = {Nicholas Matthew Boffi and Michael Samuel Albergo and Eric Vanden-Eijnden},
  journal = {Transactions on Machine Learning Research},
  year = {2025},
  url = {https://openreview.net/forum?id=cqDH0e6ak2}
}

@inproceedings{boffi2025selfdistillation,
  title = {{How to build a consistency model: Learning flow maps via self-distillation}},
  author = {Boffi, Nicholas and Albergo, Michael and Vanden-Eijnden, Eric},
  year = {2025},
  booktitle = {Advances in Neural Information Processing Systems},
  volume = {38},
  doi = {10.52202/085713-1121},
  url = {https://proceedings.neurips.cc/paper_files/paper/2025/hash/2ff3605c9e442d55156d99fe4f5f228d-Abstract-Conference.html},
  pages = {33346--33382}
}

@article{caco2,
  title = {{ADME Properties Evaluation in Drug Discovery: Prediction of Caco-2 Cell Permeability Using a Combination of NSGA-II and Boosting}},
  author = {Wang, Ning-Ning and Dong, Jie and Deng, Yin-Hua and Zhu, Min-Feng and Wen, Ming and Yao, Zhi-Jiang and Lu, Ai-Ping and Wang, Jian-Bing and Cao, Dong-Sheng},
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}

@inproceedings{campbell2022continuoustimediscrete,
  title = {{A Continuous Time Framework for Discrete Denoising Models}},
  author = {Campbell, Andrew and Benton, Joe and De Bortoli, Valentin and Rainforth, Thomas and Deligiannidis, George and Doucet, Arnaud},
  year = {2022},
  booktitle = {Advances in Neural Information Processing Systems},
  volume = {35},
  doi = {10.52202/068431-2049},
  url = {https://proceedings.neurips.cc/paper_files/paper/2022/hash/b5b528767aa35f5b1a60fe0aaeca0563-Abstract-Conference.html},
  pages = {28266--28279}
}

@inproceedings{campbell2024generativeflows,
  title = {{Generative Flows on Discrete State-Spaces: Enabling Multimodal Flows with Applications to Protein Co-Design}},
  author = {Campbell, Andrew and Yim, Jason and Barzilay, Regina and Rainforth, Tom and Jaakkola, Tommi},
  booktitle = {Proceedings of the 41st International Conference on Machine Learning},
  pages = {5453--5512},
  year = {2024},
  volume = {235},
  series = {Proceedings of Machine Learning Research},
  publisher = {PMLR},
  url = {https://proceedings.mlr.press/v235/campbell24a.html}
}

@inproceedings{cbas,
  title = {{Conditioning by adaptive sampling for robust design}},
  author = {Brookes, David and Park, Hahnbeom and Listgarten, Jennifer},
  booktitle = {Proceedings of the 36th International Conference on Machine Learning},
  pages = {773--782},
  year = {2019},
  volume = {97},
  series = {Proceedings of Machine Learning Research},
  publisher = {PMLR},
  url = {https://proceedings.mlr.press/v97/brookes19a.html}
}

@inproceedings{cgflow,
  title = {{Compositional Flows for 3{D} Molecule and Synthesis Pathway Co-design}},
  author = {Shen, Tony and Seo, Seonghwan and Irwin, Ross and Didi, Kieran and Olsson, Simon and Kim, Woo Youn and Ester, Martin},
  booktitle = {Proceedings of the 42nd International Conference on Machine Learning},
  pages = {54381--54409},
  year = {2025},
  volume = {267},
  series = {Proceedings of Machine Learning Research},
  publisher = {PMLR},
  url = {https://proceedings.mlr.press/v267/shen25b.html}
}

@inproceedings{chembo,
  title = {{ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations}},
  author = {Korovina, Ksenia and Xu, Sailun and Kandasamy, Kirthevasan and Neiswanger, Willie and Poczos, Barnabas and Schneider, Jeff and Xing, Eric},
  booktitle = {Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics},
  pages = {3393--3403},
  year = {2020},
  volume = {108},
  series = {Proceedings of Machine Learning Research},
  publisher = {PMLR},
  url = {https://proceedings.mlr.press/v108/korovina20a.html}
}

@inproceedings{chen2018neuralode,
  author = {Chen, Ricky T. Q. and Rubanova, Yulia and Bettencourt, Jesse and Duvenaud, David K},
  booktitle = {Advances in Neural Information Processing Systems},
  publisher = {Curran Associates, Inc.},
  title = {{Neural Ordinary Differential Equations}},
  url = {https://proceedings.neurips.cc/paper_files/paper/2018/file/69386f6bb1dfed68692a24c8686939b9-Paper.pdf},
  volume = {31},
  year = {2018}
}

@inproceedings{coms,
  title = {{Conservative Objective Models for Effective Offline Model-Based Optimization}},
  author = {Trabucco, Brandon and Kumar, Aviral and Geng, Xinyang and Levine, Sergey},
  booktitle = {Proceedings of the 38th International Conference on Machine Learning},
  pages = {10358--10368},
  year = {2021},
  volume = {139},
  series = {Proceedings of Machine Learning Research},
  publisher = {PMLR},
  url = {https://proceedings.mlr.press/v139/trabucco21a.html}
}

@inproceedings{designbench,
  title = {{Design-Bench: Benchmarks for Data-Driven Offline Model-Based Optimization}},
  author = {Trabucco, Brandon and Geng, Xinyang and Kumar, Aviral and Levine, Sergey},
  booktitle = {Proceedings of the 39th International Conference on Machine Learning},
  pages = {21658--21676},
  year = {2022},
  volume = {162},
  series = {Proceedings of Machine Learning Research},
  publisher = {PMLR},
  url = {https://proceedings.mlr.press/v162/trabucco22a.html}
}

@inproceedings{dsb,
  title = {{Diffusion Schr\"odinger Bridge with Applications to Score-Based Generative Modeling}},
  author = {De Bortoli, Valentin and Thornton, James and Heng, Jeremy and Doucet, Arnaud},
  year = {2021},
  booktitle = {Advances in Neural Information Processing Systems},
  volume = {34},
  url = {https://proceedings.neurips.cc/paper_files/paper/2021/hash/940392f5f32a7ade1cc201767cf83e31-Abstract.html},
  pages = {17695--17709}
}

@article{extratrees,
  title = {{Extremely randomized trees}},
  author = {Geurts, Pierre and Ernst, Damien and Wehenkel, Louis},
  journal = {Machine Learning},
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}

@inproceedings{frans2025shortcutmodels,
  title = {{One Step Diffusion via Shortcut Models}},
  author = {Frans, Kevin and Hafner, Danijar and Levine, Sergey and Abbeel, Pieter},
  year = {2025},
  booktitle = {International Conference on Learning Representations},
  url = {https://proceedings.iclr.cc/paper_files/paper/2025/hash/559a0998fab1d19b80e7e43a5852401c-Abstract-Conference.html},
  pages = {34668--34684}
}

@inproceedings{gat2024discreteflowmatching,
  title = {{Discrete Flow Matching}},
  author = {Gat, Itai and Remez, Tal and Shaul, Neta and Kreuk, Felix and Chen, Ricky T. Q. and Synnaeve, Gabriel and Adi, Yossi and Lipman, Yaron},
  year = {2024},
  booktitle = {Advances in Neural Information Processing Systems},
  volume = {37},
  doi = {10.52202/079017-4239},
  url = {https://proceedings.neurips.cc/paper_files/paper/2024/hash/f0d629a734b56a642701bba7bc8bb3ed-Abstract-Conference.html},
  pages = {133345--133385}
}

@inproceedings{gcpn,
  author = {You, Jiaxuan and Liu, Bowen and Ying, Zhitao and Pande, Vijay and Leskovec, Jure},
  booktitle = {Advances in Neural Information Processing Systems},
  publisher = {Curran Associates, Inc.},
  title = {{Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation}},
  url = {https://proceedings.neurips.cc/paper_files/paper/2018/file/d60678e8f2ba9c540798ebbde31177e8-Paper.pdf},
  volume = {31},
  year = {2018}
}

@inproceedings{geng2025meanflows,
  title = {{Mean Flows for One-step Generative Modeling}},
  author = {Geng, Zhengyang and Deng, Mingyang and Bai, Xingjian and Kolter, Zico and He, Kaiming},
  year = {2025},
  booktitle = {Advances in Neural Information Processing Systems},
  volume = {38},
  doi = {10.52202/085713-2534},
  url = {https://proceedings.neurips.cc/paper_files/paper/2025/hash/6d13e085b79d454da5910e4ca82a3d9d-Abstract-Conference.html},
  pages = {75460--75482}
}

@inproceedings{gfn,
  title = {{Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation}},
  author = {Bengio, Emmanuel and Jain, Moksh and Korablyov, Maksym and Precup, Doina and Bengio, Yoshua},
  year = {2021},
  booktitle = {Advances in Neural Information Processing Systems},
  volume = {34},
  url = {https://proceedings.neurips.cc/paper_files/paper/2021/hash/e614f646836aaed9f89ce58e837e2310-Abstract.html},
  pages = {27381--27394}
}

@article{gfnfoundations,
  author = {Yoshua Bengio and Salem Lahlou and Tristan Deleu and Edward J. Hu and Mo Tiwari and Emmanuel Bengio},
  title = {{GFlowNet Foundations}},
  journal = {Journal of Machine Learning Research},
  year = {2023},
  volume = {24},
  number = {210},
  pages = {1--55},
  url = {http://jmlr.org/papers/v24/22-0364.html}
}

@inproceedings{grammarvae,
  title = {{Grammar Variational Autoencoder}},
  author = {Matt J. Kusner and Brooks Paige and Jos{\'e} Miguel Hern{\'a}ndez-Lobato},
  booktitle = {Proceedings of the 34th International Conference on Machine Learning},
  pages = {1945--1954},
  year = {2017},
  volume = {70},
  series = {Proceedings of Machine Learning Research},
  publisher = {PMLR},
  url = {https://proceedings.mlr.press/v70/kusner17a.html}
}

@article{guacamol,
  title = {{GuacaMol: Benchmarking Models for de Novo Molecular Design}},
  author = {Brown, Nathan and Fiscato, Marco and Segler, Marwin H.S. and Vaucher, Alain C.},
  journal = {Journal of Chemical Information and Modeling},
  year = {2019},
  volume = {59},
  number = {3},
  pages = {1096--1108},
  doi = {10.1021/acs.jcim.8b00839},
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}

@inproceedings{ho2020ddpm,
  title = {{Denoising Diffusion Probabilistic Models}},
  author = {Ho, Jonathan and Jain, Ajay and Abbeel, Pieter},
  year = {2020},
  booktitle = {Advances in Neural Information Processing Systems},
  volume = {33},
  url = {https://proceedings.neurips.cc/paper_files/paper/2020/hash/4c5bcfec8584af0d967f1ab10179ca4b-Abstract.html},
  pages = {6840--6851}
}

@inproceedings{holderrieth2025generatormatching,
  title = {{Generator Matching: Generative modeling with arbitrary Markov processes}},
  author = {Holderrieth, Peter and Havasi, Marton and Yim, Jason and Shaul, Neta and Gat, Itai and Jaakkola, Tommi and Karrer, Brian and Chen, Ricky T. Q. and Lipman, Yaron},
  year = {2025},
  booktitle = {International Conference on Learning Representations},
  url = {https://proceedings.iclr.cc/paper_files/paper/2025/hash/819aaee144cb40e887a4aa9e781b1547-Abstract-Conference.html},
  pages = {52153--52219}
}

@inproceedings{holderrieth2026diamondmaps,
  title = {{Diamond Maps: Efficient Reward Alignment via Stochastic Flow Maps}},
  author = {Peter Holderrieth and Douglas Chen and Luca Eyring and Ishin Shah and Giri Anantharaman and Yutong He and Zeynep Akata and Tommi Jaakkola and Nicholas Boffi and Max Simchowitz},
  year = {2026},
  booktitle = {International Conference on Machine Learning},
  url = {https://icml.cc/virtual/2026/poster/61156}
}

@inproceedings{holderrieth2026glass,
  title = {{GLASS Flows: Efficient Inference for Reward Alignment of Flow and Diffusion Models}},
  author = {Holderrieth, Peter and Singer, Uriel and Jaakkola, Tommi and Chen, Ricky T. Q. and Lipman, Yaron and Karrer, Brian},
  year = {2026},
  booktitle = {International Conference on Learning Representations},
  url = {https://proceedings.iclr.cc/paper_files/paper/2026/hash/ad6ac52e02e14e0f2ddc0d4587ab47f1-Abstract-Conference.html},
  pages = {106232--106266}
}

@inproceedings{imf,
  title = {{Diffusion Schr\"odinger Bridge Matching}},
  author = {Shi, Yuyang and De Bortoli, Valentin and Campbell, Andrew and Doucet, Arnaud},
  year = {2023},
  booktitle = {Advances in Neural Information Processing Systems},
  volume = {36},
  doi = {10.52202/075280-2717},
  url = {https://proceedings.neurips.cc/paper_files/paper/2023/hash/c428adf74782c2092d254329b6b02482-Abstract-Conference.html},
  pages = {62183--62223}
}

@inproceedings{jtvae,
  title = {{Junction Tree Variational Autoencoder for Molecular Graph Generation}},
  author = {Jin, Wengong and Barzilay, Regina and Jaakkola, Tommi},
  booktitle = {Proceedings of the 35th International Conference on Machine Learning},
  pages = {2323--2332},
  year = {2018},
  volume = {80},
  series = {Proceedings of Machine Learning Research},
  publisher = {PMLR},
  url = {https://proceedings.mlr.press/v80/jin18a.html}
}

@inproceedings{kim2024ctm,
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