How Can I Explain This To You? An Empirical Study of Deep Neural Network Explanation Methods. Jeya Vikranth Jeyakumar, Joseph Noor, Yu-Hsi Cheng, Luis Garcia, Mani Srivastava. Advances in Neural Information Processing Systems, 2020.

@inproceedings{JeyakumarNeurIPS20,
    author    = {Jeyakumar, Jeya Vikranth and Noor, Joseph and Cheng, Yu-Hsi and Garcia, Luis and Srivastava, Mani},
    title     = {How can i explain this to you? an empirical study of deep neural network explanation methods},
    booktitle = {Advances in Neural Information Processing Systems},
    year    = {2020},
}

Verifying Performance Properties of Probabilistic Inference. Eric Atkinson, Ellie Y. Cheng, Guillaume Baudart, Louis Mandel, Michael Carbin. The Workshop on Verification of Probabilistic Programs (VeriProP), 2023.

@inproceedings{AtkinsonVeriProP23,
    author    = {Atkinson, Eric and Cheng, Ellie Y. and Baudart, Guillaume and Mandel, Louis and Carbin, Michael},
    title     = {Verifying Performance Properties of Probabilistic Inference},
    booktitle = {The Workshop on Verification of Probabilistic Programs},
    year      = {2023},
}

flip-hoisting: Exploiting Repeated Parameters in Discrete Probabilistic Programs. Yu-Hsi Cheng, Todd Millstein, Guy Van den Broeck, Steven Holtzen. International Conference on Probabilistic Programming (PROBPROG), 2021.

Extended Draft

@inproceedings{ChengPROBPROG21,
    author    = {Cheng, Yu-Hsi and Millstein, Todd and Van den Broeck, Guy and Holtzen, Steven},
    title     = {flip-hoisting: Exploiting Repeated Parameters in Discrete Probabilistic Programs},
    booktitle = {International Conference on Probabilistic Programming},
    year      = {2021},
}

Inference Plans for Dynamic Hybrid Probabilistic Inference. Ellie Y. Cheng, Eric Atkinson, Guillaume Baudart, Louis Mandel, Michael Carbin. In Submission, 2023.