Bayesian inference

Results: 1902



#Item
21Help or Hinder: Bayesian Models of Social Goal Inference Tomer D. Ullman, Chris L. Baker, Owen Macindoe, Owain Evans, Noah D. Goodman and Joshua B. Tenenbaum {tomeru, clbaker, owenm, owain, ndg, jbt}@mit.edu

Help or Hinder: Bayesian Models of Social Goal Inference Tomer D. Ullman, Chris L. Baker, Owen Macindoe, Owain Evans, Noah D. Goodman and Joshua B. Tenenbaum {tomeru, clbaker, owenm, owain, ndg, jbt}@mit.edu

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Source URL: papers.nips.cc

- Date: 2014-02-24 04:43:01
    22Exact Bayesian Inference by Symbolic Disintegration Chung-chieh Shan Norman Ramsey  Indiana University, USA

    Exact Bayesian Inference by Symbolic Disintegration Chung-chieh Shan Norman Ramsey Indiana University, USA

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    Source URL: homes.soic.indiana.edu

    - Date: 2016-11-25 21:01:47
      23LASER Summer School Università degli studi di Pavia June 25-27, 2012 Bayesian Inference in Macroeconomic Models Giorgio Primiceri Northwestern University

      LASER Summer School Università degli studi di Pavia June 25-27, 2012 Bayesian Inference in Macroeconomic Models Giorgio Primiceri Northwestern University

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      Source URL: www.laser.unimi.it

      - Date: 2012-03-07 06:00:55
        24Models, Parameters and Priors in Bayesian Inference Michael D. Lee () Department of Psychology, University of Adelaide South Australia, 5005, AUSTRALIA  Abstract

        Models, Parameters and Priors in Bayesian Inference Michael D. Lee () Department of Psychology, University of Adelaide South Australia, 5005, AUSTRALIA Abstract

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        Source URL: www.socsci.uci.edu

        - Date: 2004-10-28 21:27:44
          25Bayesian color correction method for non-colorimetric digital image sensors Xuemei Zhang , David H. Brainard Agilent Technologies Laboratories Dept. of Psychology, University of Pennsylvania Abstract

          Bayesian color correction method for non-colorimetric digital image sensors Xuemei Zhang , David H. Brainard Agilent Technologies Laboratories Dept. of Psychology, University of Pennsylvania Abstract

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          Source URL: color.psych.upenn.edu

          Language: English - Date: 2004-08-22 09:27:11
          26A Bayesian model for identifying hierarchically organised states in neural population activity Patrick Putzky1,2,3 , Florian Franzen1,2,3 , Giacomo Bassetto1,3 , Jakob H. Macke1,3 1 Max Planck Institute for Biological Cy

          A Bayesian model for identifying hierarchically organised states in neural population activity Patrick Putzky1,2,3 , Florian Franzen1,2,3 , Giacomo Bassetto1,3 , Jakob H. Macke1,3 1 Max Planck Institute for Biological Cy

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          Source URL: www.mackelab.org

          Language: English - Date: 2016-08-04 15:02:45
          27RMM Vol. 2, 2011, 79–102 Special Topic: Statistical Science and Philosophy of Science Edited by Deborah G. Mayo, Aris Spanos and Kent W. Staley http://www.rmm-journal.de/  Deborah G. Mayo

          RMM Vol. 2, 2011, 79–102 Special Topic: Statistical Science and Philosophy of Science Edited by Deborah G. Mayo, Aris Spanos and Kent W. Staley http://www.rmm-journal.de/ Deborah G. Mayo

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          Source URL: www.rmm-journal.com

          Language: English - Date: 2011-10-07 03:32:19
          28University of Vienna Vienna Graduate School of Economics Empirical Macroeconomics: Models and Methods Spring Semester 2013 Thomas A. Lubik

          University of Vienna Vienna Graduate School of Economics Empirical Macroeconomics: Models and Methods Spring Semester 2013 Thomas A. Lubik

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          Source URL: www.vgse.at

          Language: English - Date: 2013-03-07 10:47:28
          29RMM Vol. 2, 2011, 48–66 Special Topic: Statistical Science and Philosophy of Science Edited by Deborah G. Mayo, Aris Spanos and Kent W. Staley http://www.rmm-journal.de/  Stephen Senn

          RMM Vol. 2, 2011, 48–66 Special Topic: Statistical Science and Philosophy of Science Edited by Deborah G. Mayo, Aris Spanos and Kent W. Staley http://www.rmm-journal.de/ Stephen Senn

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          Source URL: www.rmm-journal.com

          Language: English - Date: 2011-09-26 02:42:15
          30Mean Field Variational Approximations in Continuous-Time Markov Processes A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science

          Mean Field Variational Approximations in Continuous-Time Markov Processes A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science

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          Source URL: www.cs.huji.ac.il

          Language: English - Date: 2015-08-10 08:23:20