Bayes By The Bay, 2013

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source: matsciencechannel     2013年5月5日

001 The essence of the Bayesian argument 1:11:40
002 An introduction to Bayesian data analysis
003 Introductory talk by Rajeeva Karandikar 45:21
004 Assigning probabilities 49:38
005 Bayesian network model for predicting protein contacts 52:44
006 Bayesian network model for predicting protein contacts 45:18
007 Bayesian models of brain function I 49:19
008 Population dynamics of Drosophila fitting a model to complex data 29:53
009 Estimating the statistical significance of sequence motifs 46:41
010 Information theory in physics and biology I 44:37
011 The application of Multiple Treatment Meta Analysis 14:16
012 Climatology and hydrology I 43:16
013 Inverse Problem Theory with examples 46:13
014 Discussion 50:21
015 Bayesian models of brain function II 49:25
016 Bayes, Kalman and tomorrow's weather 30:55
017 Bayesian network model for predicting protein contacts 1:00:42
018 Information theory in physics and biology II 37:33
020 Modeling and analysis of biopathways using dynamic Bayesian networks - I 48:45
019 Bayesian network modeling 52:49
021 Imposing Conditional Independence on Bayesian Computations 22:17
022 Climatology and hydrology II 49:34
023 Modeling and analysis of biopathways using dynamic Bayesian networks - II 46:11
024 On designing seeds for similarity search in genomic DNA 40:42
025 Dynamic response of Indian Monsoon and highintensity rain events to ENSO and Indian Ocean Dipole 24:41
026 Discretization methods for classification 40:19
027 Climatology and hydrology III 47:42
028 Earthquake Hazard in India Scientific approaches to quantification 50:20
029 A dialogue with the data 38:19