Bio

Christopher Aicher I am a fifth year statistics PhD student at the University of Washington working with Emily B. Fox.

Prior to studying at the University of Washington, I obtained a BS/MS degree in Applied Mathematics from the University of Colorado Boulder, advised by Aaron Clauset.

Research

My research interests are in scalable approximate inference methods for machine learning, specifically using deterministic Bayesian approximations (e.g. Expectation Propagation and Variational Inference) and stochastic gradient MCMC methods (e.g. SGLD).

Experience

Publications

  1. Aicher, C., Putcha, S., Nemeth, C., Fearnhead, P., & Fox, E. B. (2019). Stochastic Gradient MCMC for Nonlinear State Space Models. ArXiv Preprint ArXiv:1901.10568. [PDF] [Code]  
    BibTex
     @article{aicher2019stochastic,
      title = {Stochastic Gradient MCMC for Nonlinear State Space Models},
      author = {Aicher, Christopher and Putcha, Srshti and Nemeth, Christopher and Fearnhead, Paul and Fox, Emily B},
      journal = {arXiv preprint arXiv:1901.10568},
      year = {2019},
      month = jan,
      link = {https://arxiv.org/abs/1901.10568},
      code = {https://github.com/aicherc/sgmcmc_ssm_code}
    }
      
  2. Aicher, C., Ma, Y.-A., Foti, N. J., & Fox, E. B. (2018). Stochastic Gradient MCMC for State Space Models. ArXiv Preprint ArXiv:1810.09098. [PDF] [Code]  
    BibTex
     @article{aicher2018stochastic,
      title = {Stochastic Gradient MCMC for State Space Models},
      author = {Aicher, Christopher and Ma, Yi-An and Foti, Nicholas J. and Fox, Emily B.},
      journal = {arXiv preprint arXiv:1810.09098},
      year = {2018},
      month = oct,
      link = {https://arxiv.org/abs/1810.09098},
      code = {https://github.com/aicherc/sgmcmc_ssm_code}
    }
      
  3. Aicher, C., & Fox, E. B. (2018). Approximate Collapsed Gibbs Clustering with Expectation Propagation. ArXiv Preprint ArXiv:1807.07621. [PDF]
    BibTex
     @article{aicher2018approximate,
      title = {Approximate Collapsed Gibbs Clustering with Expectation Propagation},
      author = {Aicher, Christopher and Fox, Emily B.},
      journal = {arXiv preprint arXiv:1807.07621},
      year = {2018},
      month = jul,
      link = {https://arxiv.org/abs/1807.07621}
    }
      
  4. Simonen, K., Huang, M., Aicher, C., & Morris, P. (2018). Embodied carbon as a proxy for the environmental impact of earthquake damage repair. Energy and Buildings, 164, 131–139. [PDF]
    BibTex
     @article{simonen2018embodied,
      title = {Embodied carbon as a proxy for the environmental impact of earthquake damage repair},
      author = {Simonen, K and Huang, M and Aicher, C and Morris, P},
      journal = {Energy and Buildings},
      volume = {164},
      pages = {131--139},
      year = {2018},
      month = jan,
      link = {https://www.sciencedirect.com/science/article/pii/S0378778817319710}
    }
      
  5. Aicher, C., & Fox, E. B. (2016). Scalable clustering of correlated time series using expectation propagation. SIGKDD Workshop on MiLeTS. [PDF]
    BibTex
     @article{aicherc2016scalable,
      title = {Scalable clustering of correlated time series using expectation propagation},
      author = {Aicher, Christopher and Fox, Emily B.},
      journal = {SIGKDD Workshop on MiLeTS},
      year = {2016},
      link = {http://www-bcf.usc.edu/%7Eliu32/milets16/paper/MiLeTS_2016_paper_23.pdf}
    }
      
  6. Aicher, C., Jacobs, A. Z., & Clauset, A. (2015). Learning latent block structure in weighted networks. Journal of Complex Networks, 3(2), 221–248. [PDF] [Code]  
    BibTex
     @article{aicher2015learning,
      title = {Learning latent block structure in weighted networks},
      author = {Aicher, Christopher and Jacobs, Abigail Z and Clauset, Aaron},
      journal = {Journal of Complex Networks},
      volume = {3},
      number = {2},
      pages = {221--248},
      year = {2015},
      publisher = {Oxford University Press},
      link = {http://arxiv.org/abs/1404.0431},
      code = {http://tuvalu.santafe.edu/%7Eaaronc/wsbm/}
    }
      
  7. Aicher, C., Jacobs, A. Z., & Clauset, A. (2013). Adapting the stochastic block model to edge-weighted networks. ICML Workshop on Structured Learning. [PDF]
    BibTex
     @article{aicher2013adapting,
      title = {Adapting the stochastic block model to edge-weighted networks},
      author = {Aicher, Christopher and Jacobs, Abigail Z and Clauset, Aaron},
      journal = {ICML Workshop on Structured Learning},
      year = {2013},
      link = {http://arxiv.org/abs/1305.5782}
    }