publications

This page contains an up-to-date list of my academic publications. Unless otherwise stated, authors are ordered by contribution. An asterisk (*) denotes an equal contribution amongst co-authors. See also my Google Scholar.

Preprints

Conference Publications

  • Model Checking Finite-Horizon Markov Chains with Probabilistic Inference. Steven Holtzen*, Sebastian Junges*, Marcell Vazquez-Chanlatte, Todd Millstein, Sanjit A. Seshia, and Guy Van den Broeck. In International Conference on Computer-Aided Verification (CAV), 2021. PDF / code
    BibTex
    @inproceedings{HoltzenCAV21,
      author    = {Holtzen, Steven and Junges, Sebastian and Vazquez-Chanlatte, Marcell and Millstein, Todd and Seshia, Sanjit A. and {Van den Broeck}, Guy},
      title     = {Model Checking Finite-Horizon Markov Chains with Probabilistic Inference},
      booktitle = {Proceedings of the 33rd International Conference on Computer-Aided Verification (CAV)},
      month   = {July},
      year    = {2021}
    }
    

  • Logical Abstractions for Noisy Variational Quantum Algorithm Simulation. Yipeng Huang, Steven Holtzen, Todd Millstein, Guy Van den Broeck, and Margaret R. Martonosi. In Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2021. PDF
    BibTex
    @inproceedings{HuangASPLOS21,
      author    = {Huang, Yipeng and Holtzen, Steven and Millstein, Todd and {Van den Broeck}, Guy and Martonosi, Margaret},
      title     = {Logical Abstractions for Noisy Variational Quantum Algorithm Simulation},
      booktitle = {International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS)},
      year      = {2021},
    }
    

  • Scaling Exact Inference for Discrete Probabilistic Programs. Steven Holtzen, Guy Van den Broeck, and Todd Millstein. In Proc. ACM Program. Lang. 4 (OOPSLA), 2020. PDF / code / video / webpage / blog
    🏆 ACM SIGPLAN Distinguished Paper
    BibTex
    @inproceedings{HoltzenOOPSLA20,
      author = {Holtzen, Steven and {Van den Broeck}, Guy and Millstein, Todd},
      title = {Scaling Exact Inference for Discrete Probabilistic Programs},
      year = {2020},
      pages = {140:1--140:31},
      numpages = {31},
      booktitle={Proc. ACM Program. Lang.},
      series = {OOPSLA 2020},
      publisher = {Association for Computing Machinery},
      doi = {10.1145/3428208}
    }
    

  • On the Relationship Between Probabilistic Circuits and Determinantal Point Processes. Honghua Zhang, Steven Holtzen, and Guy Van den Broeck. In Uncertainty in Artificial Intelligence (UAI), 2020. PDF
    BibTex
    @inproceedings{ZhangUAI20,
      author    = {Zhang, Honghua and Holtzen, Steven and Van den Broeck, Guy},
      title     = {On the Relationship Between Probabilistic Circuits and Determinantal Point Processes},
      booktitle = {Proceedings of the 36th Conference on Uncertainty in Aritifical Intelligence (UAI)},
      year      = {2020},
    }
    

  • Generating and Sampling Orbits for Lifted Probabilistic Inference. Steven Holtzen, Todd Millstein, and Guy Van den Broeck. In Uncertainty in Artificial Intelligence (UAI), 2019. PDF / code / video
    BibTex
    @inproceedings{HoltzenUAI19,
      author    = {Holtzen, Steven and Millstein, Todd and Van den Broeck, Guy},
      title     = {Generating and Sampling Orbits for Lifted Probabilistic Inference},
      booktitle = {Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence (UAI)},
      month     = {jul},
      year      = {2019},
      keywords  = {conference,selective}
    }
    

  • Sound Abstraction and Decomposition of Probabilistic Programs. Steven Holtzen, Guy Van den Broeck, and Todd Millstein. In International Conference on Machine Learning (ICML), 2018. PDF
    BibTex
    @inproceedings{HoltzenICML18,
      author = {Holtzen, Steven and Van den Broeck, Guy and Millstein, Todd},
      title={Sound Abstraction and Decomposition of Probabilistic Programs},
      booktitle = {Proceedings of the 35th International Conference on Machine Learning (ICML)},
      month = Jul,
      year={2018},
    }
    

  • Probabilistic Program Abstractions. Steven Holtzen, Guy Van den Broeck, and Todd Millstein. In Uncertainty in Artificial Intelligence (UAI), 2017. PDF
    BibTex
    @inproceedings{HoltzenUAI17,
      author    = {Holtzen, Steven and Millstein, Todd and Van den Broeck, Guy},
      title     = {Probabilistic Program Abstractions},
      booktitle = {Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence (UAI)},
      month = Aug,
      year={2017},
    }
    

  • Inferring Human Intent from Video by Sampling Hierarchical Plans. Steven Holtzen*, Yibiao Zhao*, Tao Gao, Josh Tenenbaum, and Song-Chun Zhu. In IEEE International Conference on Intelligent Robots and Systems (IROS), 2016. PDF
    BibTex
    @inproceedings{holtzen2016inferring,
      title={Inferring human intent from video by sampling hierarchical plans},
      author={Holtzen, Steven and Zhao, Yibiao and Gao, Tao and Tenenbaum, Joshua B and Zhu, Song-Chun},
      booktitle={2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
      pages={1489--1496},
      year={2016},
      organization={IEEE}
    }
    

Ph.D. Thesis

Exploiting Program Structure for Scaling Probabilistic Reasoning. University of California, Los Angeles. 2021.