Evan Archer

Evan Archer

PhD Student
alumni-macke
2.A.03.a

Main Focus

I'm a graduate student researcher, working on problems at the intersection of machine learning, statistics, and computational neuroscience. I received a master's degree in applied mathematics and bachelors in electrical engineering, both from The University of Texas at Austin. You can find out more abut me at .

Curriculum Vitae

Education

  • M.S. Computational and Applied Mathematics, The University of Texas at Austin, 2010
  • B.S. Electrical Engineering, The University of Texas at Austin, 2007

Publications (, )

  • Journal Publications
    1. Archer E*, Park IM*, Pillow JW (2014). Bayesian entropy estimation for countable discrete distributionsJournal of Machine Learning Research (JMLR) [|] (accepted)
      (*=equal contribution)
    2. Archer E, Park IM, Pillow JW (2013). Bayesian and quasi-Bayesian estimators for mutual information from discrete data. Entropy, 15(5): 1738-1755. [||]
  • Conference Publications

    1. Archer E, Park IM, Pillow JW (2013). Bayesian entropy estimation for binary spike train data using parametric prior knowledge. Advances in Neural Information Processing Systems (NIPS) 26.
      (selected for spotlight presentation, top 5% of submitted) [|||]
    2. Park IM*, Archer E*, Priebe N, Pillow JW (2013). Spectral methods for neural characterization using generalized quadratic models. Advances in Neural Information Processing Systems (NIPS) 26.
      (acceptance rate: 25%; *=equal contribution) [||]
    3. Park IM, Archer E, Latimer K, Pillow JW (2013). Universal models for binary spike patterns using centered Dirichlet processes. Advances in Neural Information Processing Systems (NIPS) 26.
      (acceptance rate: 25%) [||]
    4. Archer E*, Park IM*, Pillow JW (2012). Bayesian estimation of discrete entropy with mixtures of stick-breaking priors. Advances in Neural Information Processing Systems (NIPS) 25.
      [|||] (acceptance rate: 25%; *=equal contribution)
  • Conference Abstracts
    1. Archer E, Pillow JW, Macke JH (2014). Low-d dynamical models of neural populations with common inputAreadne 2014, Santorini, Greece.
    2. Archer E, Pillow JW, Macke JH (2014). Low-dimensional models of neural population recordings with complex stimulus selectivity. Cosyne Abstracts 2014, Salt Lake City, USA.
    3. Park IM, Archer E, Latimer K, Pillow JW (2014). Scalable nonparametric models for binary spike patterns. Cosyne Abstracts 2014, Salt Lake City, USA. []
    4. Archer E, Park IM, Priebe N, Pillow JW (2013). Generalized quadratic models and moment-based dimensionality reduction. Bernstein Conference 2013, Tübingen, Germany.
    5. Park IM, Archer E, Pillow JW (2013). Bayesian entropy estimators for spike trains. CNS 2013, Paris, France. []
    6. Archer E, Park IM, Pillow JW (2013). Semi-parametric Bayesian entropy estimation for binary spike trains. Cosyne Abstracts 2013, Salt Lake City, USA. [|]
    7. Park IM, Archer E, Priebe N, Pillow JW (2013). Got a moment or two? Neural models and linear dimensionality reduction. Cosyne Abstracts 2013, Salt Lake City, USA. [|]
    8. Archer E, Park IM, Pillow JW (2012). Bayesian entropy estimation for in?nite neural alphabets. Cosyne Abstracts 2012, Salt Lake City, USA. [||]
    9. Archer E, Priebe N, Pillow JW (2011). Voltage-triggered methods for intracellular neural characterization in visual cortex. Cosyne Abstracts 2011, Salt Lake City, USA. [|]
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