Seth Flaxman

Seth Flaxman

Scalable spatiotemporal statistics and Bayesian machine learning for public policy and social science

Seth is a postdoc working on scalable methods for spatiotemporal statistics and Bayesian machine learning, applied to public policy / social science areas including crime and public health. He completed his PhD at Carnegie Mellon University in August 2015 in a program that is joint between public policy and machine learning.

Publications

2017

  • J. Runge, D. Sejdinovic, S. Flaxman, Detecting causal associations in large nonlinear time series datasets, ArXiv e-prints:1702.07007, 2017.
  • S. Flaxman, Y. W. Teh, D. Sejdinovic, Poisson Intensity Estimation with Reproducing Kernels, in Artificial Intelligence and Statistics (AISTATS), 2017.
    Project: bigbayes

2016

  • W. Herlands, A. Wilson, H. Nickisch, S. Flaxman, D. Neill, W. Van Panhuis, E. Xing, Scalable Gaussian Processes for Characterizing Multidimensional Change Surfaces, in Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016, 1013–1021.
    Project: sgmcmc
  • C. Loeffler, S. Flaxman, Is Gun Violence Contagious?, 2016.
    Project: bigbayes
  • B. Goodman, S. Flaxman, European Union regulations on algorithmic decision-making and a “right to explanation,” Jun-2016.
    Project: bigbayes
  • S. Flaxman, D. Sutherland, Y. Wang, Y. W. Teh, Understanding the 2016 US Presidential Election using ecological inference and distribution regression with census microdata, Arxiv e-prints, Nov-2016.
    Project: bigbayes
  • S. Bhatt, E. Cameron, S. Flaxman, D. J. Weiss, D. L. Smith, P. W. Gething, Improved prediction accuracy for disease risk mapping using Gaussian Process stacked generalisation, Dec-2016.
  • S. Flaxman, D. Sejdinovic, J. Cunningham, S. Filippi, Bayesian Learning of Kernel Embeddings, in Uncertainty in Artificial Intelligence (UAI), 2016, 182–191.
    Project: bigbayes
  • H. Kim, X. Lu, S. Flaxman, Y. W. Teh, Tucker Gaussian Process for Regression and Collaborative Filtering, 2016.
    Project: bigbayes

Software

2017

  • S. Flaxman, Y. W. Teh, D. Sejdinovic, Kernel Poisson. 2017.
    Project: bigbayes