Andy Shih

Google Scholar / Github / Twitter

I am a third-year PhD student in the Computer Science department at Stanford University, co-advised by Stefano Ermon and Dorsa Sadigh. I am a part of the Stanford Artificial Intelligence Laboratory (SAIL) and Stanford Statistical Machine Learning Group.

I got my BS and MS in Computer Science from UCLA, where I worked in the Automated Reasoning Group with Arthur Choi and Adnan Darwiche.

Here is my CV.

Publications

  • HyperSPNs: Compact and Expressive Probabilistic Circuits
    Andy Shih and Dorsa Sadigh and Stefano Ermon
    35th Conference on Neural Information Processing Systems, December 2021. (NeurIPS 2021)
    [bib] [code]

  • Influencing Towards Stable Multi-Agent Interactions
    Woodrow Zhouyuan Wang and Andy Shih and Annie Xie and Dorsa Sadigh
    Proceedings of the 5th Conference on Robot Learning, November 2021. (CoRL 2021)
    [bib]

  • On the Critical Role of Conventions in Adaptive Human-AI Collaboration
    Andy Shih and Arjun Sawhney and Jovana Kondic and Stefano Ermon and Dorsa Sadigh
    9th International Conference on Learning Representations, May 2021. (ICLR 2021)
    [bib] [pdf] [poster] [code] [blogpost]

  • Probabilistic Circuits for Variational Inference in Discrete Graphical Models
    Andy Shih and Stefano Ermon
    34th Conference on Neural Information Processing Systems, Vancouver, Canada, December 2020. (NeurIPS 2020)
    [bib] [pdf] [slides] [poster] [code] [blogpost]

  • On Tractable Representations of Binary Neural Networks
    Weijia Shi and Andy Shih and Adnan Darwiche and Arthur Choi
    17th International Conference on Principles of Knowledge Representation and Reasoning, Rhodes, Greece, September 2020. (KR 2020)
    [bib] [pdf]

  • On Symbolically Encoding the Behavior of Random Forests
    Arthur Choi and Andy Shih and Anchal Goyanka and Adnan Darwiche
    3rd Workshop on Formal Methods for ML-Enabled Autonomous Systems, July 2020. (FoMLAS 2020)
    [bib] [pdf]

  • Smoothing Structured Decomposable Circuits
    Andy Shih and Guy Van den Broeck and Paul Beame and Antoine Amarilli
    33rd Conference on Neural Information Processing Systems, Vancouver, Canada, December 2019. (NeurIPS 2019) [Spotlight]
    [bib] [pdf] [slides] [poster] [code]

  • Explaining Classifiers
    Andy Shih
    Master's Thesis, UCLA Department of Computer Science, 2019.
    [bib] [pdf]

  • Verifying Binarized Neural Networks by Angluin-Style Learning
    Andy Shih and Adnan Darwiche and Arthur Choi
    22nd International Conference on Theory and Applications of Satisfiability Testing, Lisbon, Portugal, July 2019. (SAT 2019)
    [bib] [pdf] [code]

  • Compiling Neural Networks into Tractable Boolean Circuits
    Arthur Choi and Weijia Shi and Andy Shih and Adnan Darwiche
    AAAI Spring Symposium on Verification of Neural Networks, Stanford University, USA, March 2019. (VNN 2019)
    [bib] [pdf]

  • Compiling Bayesian Network Classifiers into Decision Graphs
    Andy Shih and Arthur Choi and Adnan Darwiche
    33rd AAAI Conference on Artificial Intelligence, Honolulu, USA, January 2019. (AAAI 2019)
    [bib] [pdf] [code]

  • Formal Verification of Bayesian Network Classifiers
    Andy Shih and Arthur Choi and Adnan Darwiche
    9th International Conference on Probabilistic Graphical Models, Prague, Czech Republic, September 2018. (PGM 2018)
    [bib] [pdf]

  • A Symbolic Approach to Explaining Bayesian Network Classifiers
    Andy Shih and Arthur Choi and Adnan Darwiche
    27th International Joint Conference on Artificial Intelligence, Stockholm, Sweden, July 2018. (IJCAI 2018)
    [bib] [pdf] [code]



Awards

2019 UCLA Computer Science Outstanding Master's Student Award



Service

Reviewer: ICML (2020, 2021), NeurIPS (2020, 2021), ICLR (2021), CoRL (2020, 2021)

Coach: Stanford ACM-ICPC (2020-present) [new webpage!]

Contact me at

andyshih at stanford dot edu