PSYC 739301
probabilistic models of perception and cognition
spring 2014
time: tuesday and thursday, 3.305p
room: 326C (3401 walnut street, cwing)
instructor: alan stocker
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brief description
our world is a noisy world and thus, our premises and conceptions of physical reality remain subject to doubt. how do we perceive and reason in face of such uncertainty? this graduate seminar will provide a careful introduction to probability theory and the various ways it has been applied to model human perceptual and cognitive behavior.
relevant books
 e.t. janes, "Probability Theory  The Logic of Science", 2003, cambridge university press. the original book manuscript is available here. this version is almost identical to the 2003 printed edition.
 david mackay, "Information Theory, Inference, and Learning Algorithms", 2003, cambridge university press. the book can be downloaded in full here.
 judea pearl,"Causality", 2nd edition 2009, cambridge university press.
 christopher bishop,"Pattern Recognition and Machine Learning", 2006, springer.
schedule/readings/homework assignments
... will be continually updated as the semester progresses.
date   topic   readings   assignments  
jan 16  intro  
jan 21  lec: probability theory  bishop intro (pdf) and janyes intro excerpt (pdf) 
  
jan 23  lec: probability theory    homework 1  
jan 28  lec: probability theory      
jan 30  lec: bayesian signal detection theory  SDT handout by d.heeger (pdf) matlab script (mfile) 
turn in hw 1  
feb 04  lec: graphical models  bishop chap 8 excerpt (pdf)  homework 2  
feb 06  lec: graphical models examples lec: bayesian estimation 
    
feb 11  lec: bayesian 2AFC  stocker/simoncelli2006 (pdf)    
feb 12  no class  
feb 18  lec: cue integration maxlikelihood fitting 
ernst/banks2002 (pdf) and koerding_etal2007 (pdf) 
homework 3  
feb 20  lec: cue integration continued      
feb 25  lec: conditioned perception  jazayeri/movshon2007 (pdf) and stocker/simoncelli2008 (pdf) 
  
feb 27  no class    homework 4 data (ex4Data.mat) 

mar 4  case studies  ashourian/loewenstein2011 (pdf) jazayeri/shadlen2010 (pdf) 
  
mar 6  more case studies  vandenBerg/etal2012 (pdf) knill2007 (pdf) 
  
mar 11/13  spring break    select your project!  
mar 18  pres: present your selected projects    hand in homework 4  
mar 20  pres: present your selected projects.      
mar 25  lec: causality and intervention      
mar 27  lec: neural models of probabilistic inference 
jazayeri/movshon2006 (pdf) and ma/etal2006 (pdf) and rust/stocker2010 (pdf) 
  
apr 01  lec: neural models cont'ed  ganguli/simoncelli2011 (pdf) and wei/stocker2012 (pdf) 
  
apr 03  lec: neural models cont'ed  berkes_etal2010 (pdf)    
apr 08  individual meetings      
apr 10  individual meetings      
apr 15  lec: learning in probabilistic systems      
apr 17  lec: learning in probabilistic systems  schulz/gopnik/glymour2007 (pdf) hagmayer et al. 2010 (pdf) 
  
apr 22  pres: final project presentations! max. 15 mins each 
    
apr 24  pres: final project presentations!      
apr 29  pres: final project presentations!      
may 04  final report due.     