589689.xyz

Coursera - Probabilistic Graphical Models

  • 收录时间:2018-03-17 07:38:06
  • 文件大小:1GB
  • 下载次数:344
  • 最近下载:2021-01-15 18:18:28
  • 磁力链接:
立即下载 复制链接

文件列表

  1. Lectures/Week 7 - 19 Learning- Parameter Estimation in MNs/01_Maximum_Likelihood_for_Log-Linear_Models_28-47.mp4 35MB
  2. Lectures/Week 9 - 23 Summary/01_Class_Summary_24-38.mp4 32MB
  3. Lectures/Week 6 - 15 Decision Theory/01_Maximum_Expected_Utility_25-57.mp4 29MB
  4. Lectures/Week 8 - 20 Structure Learning/06_Learning_General_Graphs-_Heuristic_Search_23-36.mp4 27MB
  5. Lectures/Week 9 - 21 Learning With Incomplete Data/05_Latent_Variables_22-00.mp4 27MB
  6. Lectures/Week 1 - 03 Template Models/02_Temporal_Models_-_DBNs_23-02.mp4 26MB
  7. Lectures/Week 2 - 06 Markov Network Fundamentals/06_Log-Linear_Models_22-08.mp4 26MB
  8. Lectures/Week 9 - 22 Learning- Wrapup/01_Summary-_Learning_20-11.mp4 26MB
  9. Lectures/Week 2 - 06 Markov Network Fundamentals/03_Conditional_Random_Fields_22-22.mp4 25MB
  10. Lectures/Week 9 - 21 Learning With Incomplete Data/01_Learning_With_Incomplete_Data_-_Overview_21-34.mp4 25MB
  11. Lectures/Week 3 - 07 Representation Wrapup-Knowledge Engineering/01_Knowledge_Engineering_23-05.mp4 25MB
  12. Lectures/Week 6 - 14 Inference- Temporal Models and Wrap-up/01_Inference_in_Temporal_Models_19-43.mp4 23MB
  13. Lectures/Week 1 - 01 Introduction and Overview/02_Overview_and_Motivation_19-17.mp4 23MB
  14. Lectures/Week 8 - 20 Structure Learning/04_Bayesian_Scores_20-35.mp4 23MB
  15. Lectures/Week 1 - 03 Template Models/04_Plate_Models_20-08.mp4 22MB
  16. Lectures/Week 2 - 06 Markov Network Fundamentals/05_I-maps_and_perfect_maps_20-59.mp4 22MB
  17. Lectures/Week 1 - 02 Bayesian Network Fundamentals/05_Independencies_in_Bayesian_Networks_18-18.mp4 22MB
  18. Lectures/Week 7 - 18 Learning- Parameter Estimation in BNs/05_Bayesian_Estimation_for_Bayesian_Networks_17-02.mp4 21MB
  19. Lectures/Week 1 - 04 ML-class Octave Tutorial/02_Moving_Data_Around_16-07.mp4 21MB
  20. Lectures/Week 6 - 15 Decision Theory/02_Utility_Functions_18-15.mp4 20MB
  21. Lectures/Week 1 - 02 Bayesian Network Fundamentals/01_Semantics__Factorization_17-20.mp4 20MB
  22. Lectures/Week 6 - 15 Decision Theory/03_Value_of_Perfect_Information_17-14.mp4 19MB
  23. Lectures/Week 2 - 06 Markov Network Fundamentals/02_General_Gibbs_Distribution_15-52.mp4 19MB
  24. Lectures/Week 8 - 20 Structure Learning/02_Likelihood_Scores_16-49.mp4 19MB
  25. Lectures/Week 7 - 18 Learning- Parameter Estimation in BNs/03_Bayesian_Estimation_15-27.mp4 19MB
  26. Lectures/Week 9 - 21 Learning With Incomplete Data/02_Expectation_Maximization_-_Intro_16-17.mp4 18MB
  27. Lectures/Week 1 - 04 ML-class Octave Tutorial/01_Basic_Operations_13-59.mp4 18MB
  28. Lectures/Week 7 - 18 Learning- Parameter Estimation in BNs/02_Maximum_Likelihood_Estimation_for_Bayesian_Networks_15-49.mp4 18MB
  29. Lectures/Week 8 - 20 Structure Learning/07_Learning_General_Graphs-_Search_and_Decomposability_15-46.mp4 18MB
  30. Lectures/Week 6 - 17 Learning-Overview/01_Learning-_Overview_15-35.mp4 18MB
  31. Lectures/Week 5 - 13 Inference- Sampling Methods/05_Metropolis_Hastings_Algorithm_27-06.mp4 17MB
  32. Lectures/Week 1 - 04 ML-class Octave Tutorial/05_Control_Statements-_for_while_if_statements_12-55.mp4 16MB
  33. Lectures/Week 7 - 18 Learning- Parameter Estimation in BNs/04_Bayesian_Prediction_13-40.mp4 16MB
  34. Lectures/Week 1 - 04 ML-class Octave Tutorial/06_Vectorization_13-48.mp4 16MB
  35. Lectures/Week 2 - 05 Structured CPDs/02_Tree-Structured_CPDs_14-37.mp4 16MB
  36. Lectures/Week 2 - 05 Structured CPDs/03_Independence_of_Causal_Influence_13-08.mp4 16MB
  37. Lectures/Week 1 - 02 Bayesian Network Fundamentals/04_Conditional_Independence_12-38.mp4 16MB
  38. Lectures/Week 1 - 02 Bayesian Network Fundamentals/03_Flow_of_Probabilistic_Influence_14-36.mp4 15MB
  39. Lectures/Week 2 - 05 Structured CPDs/04_Continuous_Variables_13-25.mp4 15MB
  40. Lectures/Week 1 - 04 ML-class Octave Tutorial/03_Computing_On_Data_13-15.mp4 15MB
  41. Lectures/Week 7 - 18 Learning- Parameter Estimation in BNs/01_Maximum_Likelihood_Estimation_14-59.mp4 15MB
  42. Lectures/Week 7 - 19 Learning- Parameter Estimation in MNs/02_Maximum_Likelihood_for_Conditional_Random_Fields_13-24.mp4 15MB
  43. Lectures/Week 3 - 08 Inference-Variable Elimination/04_Complexity_of_Variable_Elimination_12-48.mp4 15MB
  44. Lectures/Week 8 - 20 Structure Learning/05_Learning_Tree_Structured_Networks_12-05.mp4 14MB
  45. Lectures/Week 6 - 14 Inference- Temporal Models and Wrap-up/02_Inference-_Summary_12-45.mp4 14MB
  46. Lectures/Week 6 - 16 ML-class Revision/04_Model_Selection_and_Train_Validation_Test_Sets_12-03.mp4 14MB
  47. Lectures/Week 5 - 13 Inference- Sampling Methods/01_Simple_Sampling_23-37.mp4 14MB
  48. Lectures/Week 1 - 03 Template Models/03_Temporal_Models_-_HMMs_12-01.mp4 14MB
  49. Lectures/Week 1 - 04 ML-class Octave Tutorial/04_Plotting_Data_09-38.mp4 13MB
  50. Lectures/Week 3 - 09 Inference-Belief Propagation Part 1/01_Belief_Propagation_21-21.mp4 13MB
  51. Lectures/Week 4 - 10 Inference-Belief Propagation Part 2/07_Loopy_BP_and_Message_Decoding_21-42.mp4 13MB
  52. Lectures/Week 9 - 21 Learning With Incomplete Data/03_Analysis_of_EM_Algorithm_11-32.mp4 13MB
  53. Lectures/Week 1 - 02 Bayesian Network Fundamentals/08_Knowledge_Engineering_Example_-_SAMIAM_14-14.mp4 13MB
  54. Lectures/Week 9 - 21 Learning With Incomplete Data/04_EM_in_Practice_11-17.mp4 13MB
  55. Lectures/Week 4 - 11 Inference-MAP Estimation Part 1/01_Max_Sum_Message_Passing_20-27.mp4 13MB
  56. Lectures/Week 6 - 16 ML-class Revision/06_Regularization_and_Bias_Variance_11-20.mp4 13MB
  57. Lectures/Week 2 - 06 Markov Network Fundamentals/01_Pairwise_Markov_Networks_10-59.mp4 13MB
  58. Lectures/Week 8 - 20 Structure Learning/03_BIC_and_Asymptotic_Consistency_11-26.mp4 13MB
  59. Lectures/Week 5 - 13 Inference- Sampling Methods/04_Gibbs_Sampling_19-26.mp4 13MB
  60. Lectures/Week 6 - 16 ML-class Revision/02_Regularization-_Cost_Function_10-10.mp4 12MB
  61. Lectures/Week 1 - 03 Template Models/01_Overview_of_Template_Models_10-55.mp4 12MB
  62. Lectures/Week 1 - 02 Bayesian Network Fundamentals/07_Application_-_Medical_Diagnosis_09-19.mp4 12MB
  63. Lectures/Week 7 - 19 Learning- Parameter Estimation in MNs/03_MAP_Estimation_for_MRFs_and_CRFs_9-59.mp4 11MB
  64. Lectures/Week 5 - 12 Inference- MAP Estimation Part 2/02_Dual_Decomposition_-_Intuition_17-46.mp4 11MB
  65. Lectures/Week 6 - 16 ML-class Revision/01_Regularization-_The_Problem_of_Overfitting_09-42.mp4 11MB
  66. Lectures/Week 3 - 08 Inference-Variable Elimination/03_Variable_Elimination_Algorithm_16-17.mp4 11MB
  67. Lectures/Week 1 - 02 Bayesian Network Fundamentals/02_Reasoning_Patterns_09-59.mp4 11MB
  68. Lectures/Week 1 - 02 Bayesian Network Fundamentals/06_Naive_Bayes_09-52.mp4 11MB
  69. Lectures/Week 4 - 10 Inference-Belief Propagation Part 2/05_Clique_Trees_and_VE_16-17.mp4 11MB
  70. Lectures/Week 4 - 10 Inference-Belief Propagation Part 2/02_Clique_Tree_Algorithm_-_Correctness_18-23.mp4 10MB
  71. Lectures/Week 2 - 06 Markov Network Fundamentals/07_Shared_Features_in_Log-Linear_Models_08-28.mp4 10MB
  72. Lectures/Week 5 - 12 Inference- MAP Estimation Part 2/03_Dual_Decomposition_-_Algorithm_16-16.mp4 10MB
  73. Lectures/Week 3 - 09 Inference-Belief Propagation Part 1/02_Properties_of_Cluster_Graphs_15-00.mp4 10MB
  74. Lectures/Week 5 - 12 Inference- MAP Estimation Part 2/01_Tractable_MAP_Problems_15-04.mp4 10MB
  75. Lectures/Week 2 - 05 Structured CPDs/01_Overview-_Structured_CPDs_08-00.mp4 10MB
  76. Lectures/Week 3 - 08 Inference-Variable Elimination/05_Graph-Based_Perspective_on_Variable_Elimination_15-25.mp4 10MB
  77. Lectures/Week 5 - 13 Inference- Sampling Methods/03_Using_a_Markov_Chain_15-27.mp4 10MB
  78. Lectures/Week 4 - 10 Inference-Belief Propagation Part 2/04_Clique_Trees_and_Independence_15-21.mp4 10MB
  79. Lectures/Week 5 - 13 Inference- Sampling Methods/02_Markov_Chain_Monte_Carlo_14-18.mp4 9MB
  80. Lectures/Week 4 - 10 Inference-Belief Propagation Part 2/06_BP_In_Practice_15-38.mp4 9MB
  81. Lectures/Week 3 - 08 Inference-Variable Elimination/01_Overview-_Conditional_Probability_Queries_15-22.mp4 9MB
  82. Lectures/Week 6 - 16 ML-class Revision/05_Diagnosing_Bias_vs_Variance_07-42.mp4 9MB
  83. Lectures/Week 3 - 08 Inference-Variable Elimination/06_Finding_Elimination_Orderings_11-58.mp4 9MB
  84. Lectures/Week 4 - 10 Inference-Belief Propagation Part 2/03_Clique_Tree_Algorithm_-_Computation_16-18.mp4 9MB
  85. Lectures/Week 6 - 16 ML-class Revision/03_Evaluating_a_Hypothesis_07-35.mp4 8MB
  86. Lectures/Week 1 - 01 Introduction and Overview/04_Factors_06-40.mp4 7MB
  87. Lectures/Week 1 - 01 Introduction and Overview/01_Welcome_05-35.mp4 7MB
  88. Lectures/Week 8 - 20 Structure Learning/01_Structure_Learning_Overview_5-49.mp4 7MB
  89. Lectures/Week 3 - 08 Inference-Variable Elimination/02_Overview-_MAP_Inference_09-42.mp4 6MB
  90. Lectures/Week 2 - 06 Markov Network Fundamentals/04_Independencies_in_Markov_Networks_04-48.mp4 6MB
  91. Lectures/Week 1 - 01 Introduction and Overview/03_Distributions_04-56.mp4 6MB
  92. Lectures/Week 4 - 10 Inference-Belief Propagation Part 2/01_Properties_of_Belief_Propagation_9-31.mp4 6MB
  93. Lectures/Week 1 - 04 ML-class Octave Tutorial/07_Working_on_and_Submitting_Programming_Exercises_03-33.mp4 5MB
  94. Assignments/Assignment 3/inference/doinference.exe 3MB
  95. Lectures/Week 4 - 11 Inference-MAP Estimation Part 1/02_Finding_a_MAP_Assignment_3-57.mp4 3MB
  96. Assignments/Assignment 9/PA9Data.mat 3MB
  97. Assignments/Assignment 3/inference/doinference-linux 2MB
  98. Assignments/Assignment 3/inference/inference-src.zip 2MB
  99. Assignments/Assignment 2/PA2Description.pdf 1MB
  100. Assignments/Assignment 9/PA9SampleCases.mat 1MB
  101. Assignments/Assignment 9/PA9Description.pdf 987KB
  102. Assignments/Assignment 9/submit_input.mat 842KB
  103. Assignments/Assignment 3/inference/doinference-mac 816KB
  104. Assignments/Assignment 5/Assignment 5.pdf 522KB
  105. Assignments/Assignment 7/PA7Description.pdf 487KB
  106. Assignments/Assignment 6/Assignment 6.pdf 456KB
  107. Assignments/Assignment 8/submit_input.mat 453KB
  108. Assignments/Assignment 4/Assignment 4.pdf 421KB
  109. Assignments/Assignment 3/PA3Description.pdf 413KB
  110. Assignments/Assignment 8/PA8Description.pdf 378KB
  111. Assignments/Assignment 8/PA8SampleCases.mat 288KB
  112. Assignments/Assignment 1/Assignment 1.pdf 276KB
  113. Assignments/Assignment 4/PA4Sample.mat 215KB
  114. Assignments/Assignment 8/PA8Data.mat 191KB
  115. Assignments/Assignment 2/PA2Appendix.pdf 98KB
  116. Assignments/Assignment 7/Part2Sample.mat 85KB
  117. Assignments/Assignment 3/PA3SampleCases.mat 74KB
  118. Assignments/Assignment 4/PA4Test.mat 63KB
  119. Assignments/Assignment 3/PA3Models.mat 54KB
  120. Assignments/Assignment 5/exampleIOPA5.mat 44KB
  121. Assignments/Assignment 5/submit.m 37KB
  122. Lectures/Week 5 - 13 Inference- Sampling Methods/05_Metropolis_Hastings_Algorithm_27-06.srt 32KB
  123. Lectures/Week 7 - 19 Learning- Parameter Estimation in MNs/01_Maximum_Likelihood_for_Log-Linear_Models_28-47.srt 31KB
  124. Lectures/Week 8 - 20 Structure Learning/06_Learning_General_Graphs-_Heuristic_Search_23-36.srt 30KB
  125. Lectures/Week 6 - 15 Decision Theory/01_Maximum_Expected_Utility_25-57.srt 30KB
  126. Assignments/Assignment 6/submit.m 28KB
  127. Assignments/Assignment 4/submit.m 28KB
  128. Lectures/Week 3 - 07 Representation Wrapup-Knowledge Engineering/01_Knowledge_Engineering_23-05.srt 28KB
  129. Lectures/Week 2 - 06 Markov Network Fundamentals/06_Log-Linear_Models_22-08.srt 27KB
  130. Lectures/Week 4 - 10 Inference-Belief Propagation Part 2/07_Loopy_BP_and_Message_Decoding_21-42.srt 27KB
  131. Lectures/Week 1 - 03 Template Models/02_Temporal_Models_-_DBNs_23-02.srt 26KB
  132. Assignments/Assignment 2/submit.m 26KB
  133. Lectures/Week 5 - 13 Inference- Sampling Methods/01_Simple_Sampling_23-37.srt 26KB
  134. Lectures/Week 9 - 21 Learning With Incomplete Data/05_Latent_Variables_22-00.srt 25KB
  135. Lectures/Week 6 - 14 Inference- Temporal Models and Wrap-up/01_Inference_in_Temporal_Models_19-43.srt 25KB
  136. Lectures/Week 1 - 01 Introduction and Overview/02_Overview_and_Motivation_19-17.srt 25KB
  137. Lectures/Week 9 - 21 Learning With Incomplete Data/01_Learning_With_Incomplete_Data_-_Overview_21-34.srt 25KB
  138. Assignments/Assignment 8/submit.m 24KB
  139. Lectures/Week 3 - 09 Inference-Belief Propagation Part 1/01_Belief_Propagation_21-21.srt 24KB
  140. Lectures/Week 8 - 20 Structure Learning/04_Bayesian_Scores_20-35.srt 24KB
  141. Lectures/Week 1 - 03 Template Models/04_Plate_Models_20-08.srt 23KB
  142. Lectures/Week 2 - 06 Markov Network Fundamentals/03_Conditional_Random_Fields_22-22.srt 23KB
  143. Lectures/Week 1 - 02 Bayesian Network Fundamentals/08_Knowledge_Engineering_Example_-_SAMIAM_14-14.srt 23KB
  144. Lectures/Week 1 - 02 Bayesian Network Fundamentals/05_Independencies_in_Bayesian_Networks_18-18.srt 23KB
  145. Assignments/Assignment 1/submit.m 22KB
  146. Lectures/Week 2 - 06 Markov Network Fundamentals/05_I-maps_and_perfect_maps_20-59.srt 22KB
  147. Lectures/Week 4 - 11 Inference-MAP Estimation Part 1/01_Max_Sum_Message_Passing_20-27.srt 22KB
  148. Lectures/Week 5 - 13 Inference- Sampling Methods/05_Metropolis_Hastings_Algorithm_27-06.txt 22KB
  149. Assignments/Assignment 9/submit.m 22KB
  150. Lectures/Week 6 - 15 Decision Theory/03_Value_of_Perfect_Information_17-14.srt 22KB
  151. Lectures/Week 7 - 19 Learning- Parameter Estimation in MNs/01_Maximum_Likelihood_for_Log-Linear_Models_28-47.txt 21KB
  152. Lectures/Week 1 - 02 Bayesian Network Fundamentals/01_Semantics__Factorization_17-20.srt 21KB
  153. Lectures/Week 6 - 15 Decision Theory/02_Utility_Functions_18-15.srt 21KB
  154. Lectures/Week 8 - 20 Structure Learning/06_Learning_General_Graphs-_Heuristic_Search_23-36.txt 21KB
  155. Assignments/Assignment 3/submit.m 21KB
  156. Assignments/Assignment 7/submit.m 20KB
  157. Lectures/Week 6 - 15 Decision Theory/01_Maximum_Expected_Utility_25-57.txt 20KB
  158. Lectures/Week 4 - 10 Inference-Belief Propagation Part 2/02_Clique_Tree_Algorithm_-_Correctness_18-23.srt 20KB
  159. Lectures/Week 9 - 21 Learning With Incomplete Data/02_Expectation_Maximization_-_Intro_16-17.srt 20KB
  160. Lectures/Week 5 - 12 Inference- MAP Estimation Part 2/02_Dual_Decomposition_-_Intuition_17-46.srt 20KB
  161. Lectures/Week 5 - 13 Inference- Sampling Methods/04_Gibbs_Sampling_19-26.srt 20KB
  162. Lectures/Week 6 - 17 Learning-Overview/01_Learning-_Overview_15-35.srt 19KB
  163. Lectures/Week 5 - 12 Inference- MAP Estimation Part 2/01_Tractable_MAP_Problems_15-04.srt 19KB
  164. Lectures/Week 7 - 18 Learning- Parameter Estimation in BNs/05_Bayesian_Estimation_for_Bayesian_Networks_17-02.srt 19KB
  165. Lectures/Week 8 - 20 Structure Learning/02_Likelihood_Scores_16-49.srt 19KB
  166. Lectures/Week 1 - 04 ML-class Octave Tutorial/02_Moving_Data_Around_16-07.srt 19KB
  167. Lectures/Week 5 - 12 Inference- MAP Estimation Part 2/03_Dual_Decomposition_-_Algorithm_16-16.srt 18KB
  168. Lectures/Week 3 - 07 Representation Wrapup-Knowledge Engineering/01_Knowledge_Engineering_23-05.txt 18KB
  169. Assignments/Assignment 7/Part2Test.mat 18KB
  170. Lectures/Week 4 - 10 Inference-Belief Propagation Part 2/07_Loopy_BP_and_Message_Decoding_21-42.txt 18KB
  171. Lectures/Week 1 - 03 Template Models/02_Temporal_Models_-_DBNs_23-02.txt 18KB
  172. Lectures/Week 5 - 13 Inference- Sampling Methods/01_Simple_Sampling_23-37.txt 18KB
  173. Lectures/Week 5 - 13 Inference- Sampling Methods/03_Using_a_Markov_Chain_15-27.srt 18KB
  174. Lectures/Week 7 - 18 Learning- Parameter Estimation in BNs/03_Bayesian_Estimation_15-27.srt 18KB
  175. Lectures/Week 4 - 10 Inference-Belief Propagation Part 2/05_Clique_Trees_and_VE_16-17.srt 18KB
  176. Lectures/Week 3 - 08 Inference-Variable Elimination/03_Variable_Elimination_Algorithm_16-17.srt 18KB
  177. Lectures/Week 3 - 08 Inference-Variable Elimination/01_Overview-_Conditional_Probability_Queries_15-22.srt 17KB
  178. Lectures/Week 4 - 10 Inference-Belief Propagation Part 2/06_BP_In_Practice_15-38.srt 17KB
  179. Lectures/Week 9 - 21 Learning With Incomplete Data/05_Latent_Variables_22-00.txt 17KB
  180. Lectures/Week 5 - 13 Inference- Sampling Methods/02_Markov_Chain_Monte_Carlo_14-18.srt 17KB
  181. Lectures/Week 4 - 10 Inference-Belief Propagation Part 2/04_Clique_Trees_and_Independence_15-21.srt 17KB
  182. Lectures/Week 6 - 14 Inference- Temporal Models and Wrap-up/01_Inference_in_Temporal_Models_19-43.txt 17KB
  183. Lectures/Week 1 - 01 Introduction and Overview/02_Overview_and_Motivation_19-17.txt 17KB
  184. Lectures/Week 9 - 21 Learning With Incomplete Data/01_Learning_With_Incomplete_Data_-_Overview_21-34.txt 17KB
  185. Lectures/Week 2 - 05 Structured CPDs/02_Tree-Structured_CPDs_14-37.srt 17KB
  186. Lectures/Week 7 - 18 Learning- Parameter Estimation in BNs/02_Maximum_Likelihood_Estimation_for_Bayesian_Networks_15-49.srt 17KB
  187. Lectures/Week 1 - 04 ML-class Octave Tutorial/06_Vectorization_13-48.srt 17KB
  188. Lectures/Week 2 - 06 Markov Network Fundamentals/06_Log-Linear_Models_22-08.txt 17KB
  189. Lectures/Week 3 - 09 Inference-Belief Propagation Part 1/02_Properties_of_Cluster_Graphs_15-00.srt 17KB
  190. Lectures/Week 1 - 04 ML-class Octave Tutorial/01_Basic_Operations_13-59.srt 16KB
  191. Lectures/Week 6 - 14 Inference- Temporal Models and Wrap-up/02_Inference-_Summary_12-45.srt 16KB
  192. Lectures/Week 3 - 09 Inference-Belief Propagation Part 1/01_Belief_Propagation_21-21.txt 16KB
  193. Lectures/Week 8 - 20 Structure Learning/04_Bayesian_Scores_20-35.txt 16KB
  194. Lectures/Week 2 - 06 Markov Network Fundamentals/02_General_Gibbs_Distribution_15-52.srt 16KB
  195. Lectures/Week 4 - 10 Inference-Belief Propagation Part 2/03_Clique_Tree_Algorithm_-_Computation_16-18.srt 16KB
  196. Lectures/Week 6 - 16 ML-class Revision/04_Model_Selection_and_Train_Validation_Test_Sets_12-03.srt 16KB
  197. Lectures/Week 1 - 03 Template Models/04_Plate_Models_20-08.txt 16KB
  198. Lectures/Week 2 - 06 Markov Network Fundamentals/03_Conditional_Random_Fields_22-22.txt 16KB
  199. Lectures/Week 1 - 04 ML-class Octave Tutorial/03_Computing_On_Data_13-15.srt 16KB
  200. Lectures/Week 7 - 19 Learning- Parameter Estimation in MNs/02_Maximum_Likelihood_for_Conditional_Random_Fields_13-24.srt 16KB
  201. Lectures/Week 1 - 02 Bayesian Network Fundamentals/05_Independencies_in_Bayesian_Networks_18-18.txt 16KB
  202. Lectures/Week 1 - 02 Bayesian Network Fundamentals/03_Flow_of_Probabilistic_Influence_14-36.srt 15KB
  203. Lectures/Week 7 - 18 Learning- Parameter Estimation in BNs/01_Maximum_Likelihood_Estimation_14-59.srt 15KB
  204. Lectures/Week 4 - 11 Inference-MAP Estimation Part 1/01_Max_Sum_Message_Passing_20-27.txt 15KB
  205. Lectures/Week 2 - 06 Markov Network Fundamentals/05_I-maps_and_perfect_maps_20-59.txt 15KB
  206. Lectures/Week 9 - 21 Learning With Incomplete Data/04_EM_in_Practice_11-17.srt 15KB
  207. Lectures/Week 1 - 03 Template Models/03_Temporal_Models_-_HMMs_12-01.srt 15KB
  208. Lectures/Week 1 - 04 ML-class Octave Tutorial/05_Control_Statements-_for_while_if_statements_12-55.srt 15KB
  209. Lectures/Week 7 - 18 Learning- Parameter Estimation in BNs/04_Bayesian_Prediction_13-40.srt 15KB
  210. Lectures/Week 1 - 02 Bayesian Network Fundamentals/04_Conditional_Independence_12-38.srt 15KB
  211. Lectures/Week 6 - 15 Decision Theory/03_Value_of_Perfect_Information_17-14.txt 15KB
  212. Lectures/Week 6 - 16 ML-class Revision/06_Regularization_and_Bias_Variance_11-20.srt 15KB
  213. Lectures/Week 3 - 08 Inference-Variable Elimination/05_Graph-Based_Perspective_on_Variable_Elimination_15-25.srt 15KB
  214. Lectures/Week 2 - 05 Structured CPDs/04_Continuous_Variables_13-25.srt 15KB
  215. Lectures/Week 1 - 02 Bayesian Network Fundamentals/01_Semantics__Factorization_17-20.txt 14KB
  216. Assignments/Assignment 3/PA3Data.mat 14KB
  217. Lectures/Week 6 - 15 Decision Theory/02_Utility_Functions_18-15.txt 14KB
  218. Lectures/Week 3 - 08 Inference-Variable Elimination/06_Finding_Elimination_Orderings_11-58.srt 14KB
  219. Lectures/Week 8 - 20 Structure Learning/05_Learning_Tree_Structured_Networks_12-05.srt 14KB
  220. Lectures/Week 2 - 05 Structured CPDs/03_Independence_of_Causal_Influence_13-08.srt 14KB
  221. Lectures/Week 9 - 21 Learning With Incomplete Data/02_Expectation_Maximization_-_Intro_16-17.txt 14KB
  222. Lectures/Week 4 - 10 Inference-Belief Propagation Part 2/02_Clique_Tree_Algorithm_-_Correctness_18-23.txt 14KB
  223. Lectures/Week 8 - 20 Structure Learning/03_BIC_and_Asymptotic_Consistency_11-26.srt 14KB
  224. Lectures/Week 2 - 06 Markov Network Fundamentals/01_Pairwise_Markov_Networks_10-59.srt 13KB
  225. Lectures/Week 5 - 12 Inference- MAP Estimation Part 2/02_Dual_Decomposition_-_Intuition_17-46.txt 13KB
  226. Lectures/Week 5 - 13 Inference- Sampling Methods/04_Gibbs_Sampling_19-26.txt 13KB
  227. Lectures/Week 6 - 17 Learning-Overview/01_Learning-_Overview_15-35.txt 13KB
  228. Lectures/Week 9 - 21 Learning With Incomplete Data/03_Analysis_of_EM_Algorithm_11-32.srt 13KB
  229. Lectures/Week 7 - 18 Learning- Parameter Estimation in BNs/05_Bayesian_Estimation_for_Bayesian_Networks_17-02.txt 13KB
  230. Lectures/Week 5 - 12 Inference- MAP Estimation Part 2/01_Tractable_MAP_Problems_15-04.txt 13KB
  231. Lectures/Week 6 - 16 ML-class Revision/01_Regularization-_The_Problem_of_Overfitting_09-42.srt 13KB
  232. Lectures/Week 8 - 20 Structure Learning/02_Likelihood_Scores_16-49.txt 13KB
  233. Lectures/Week 3 - 08 Inference-Variable Elimination/04_Complexity_of_Variable_Elimination_12-48.srt 13KB
  234. Lectures/Week 6 - 16 ML-class Revision/02_Regularization-_Cost_Function_10-10.srt 13KB
  235. Lectures/Week 1 - 04 ML-class Octave Tutorial/02_Moving_Data_Around_16-07.txt 13KB
  236. Lectures/Week 1 - 03 Template Models/01_Overview_of_Template_Models_10-55.srt 13KB
  237. Lectures/Week 5 - 12 Inference- MAP Estimation Part 2/03_Dual_Decomposition_-_Algorithm_16-16.txt 13KB
  238. Lectures/Week 1 - 02 Bayesian Network Fundamentals/08_Knowledge_Engineering_Example_-_SAMIAM_14-14.txt 12KB
  239. Lectures/Week 7 - 19 Learning- Parameter Estimation in MNs/03_MAP_Estimation_for_MRFs_and_CRFs_9-59.srt 12KB
  240. Lectures/Week 5 - 13 Inference- Sampling Methods/03_Using_a_Markov_Chain_15-27.txt 12KB
  241. Lectures/Week 4 - 10 Inference-Belief Propagation Part 2/05_Clique_Trees_and_VE_16-17.txt 12KB
  242. Lectures/Week 7 - 18 Learning- Parameter Estimation in BNs/03_Bayesian_Estimation_15-27.txt 12KB
  243. Lectures/Week 1 - 02 Bayesian Network Fundamentals/07_Application_-_Medical_Diagnosis_09-19.srt 12KB
  244. Lectures/Week 3 - 08 Inference-Variable Elimination/03_Variable_Elimination_Algorithm_16-17.txt 12KB
  245. Lectures/Week 3 - 08 Inference-Variable Elimination/01_Overview-_Conditional_Probability_Queries_15-22.txt 12KB
  246. Lectures/Week 1 - 02 Bayesian Network Fundamentals/02_Reasoning_Patterns_09-59.srt 12KB
  247. Lectures/Week 4 - 10 Inference-Belief Propagation Part 2/06_BP_In_Practice_15-38.txt 12KB
  248. Lectures/Week 5 - 13 Inference- Sampling Methods/02_Markov_Chain_Monte_Carlo_14-18.txt 12KB
  249. Lectures/Week 4 - 10 Inference-Belief Propagation Part 2/04_Clique_Trees_and_Independence_15-21.txt 12KB
  250. Lectures/Week 2 - 05 Structured CPDs/02_Tree-Structured_CPDs_14-37.txt 11KB
  251. Lectures/Week 7 - 18 Learning- Parameter Estimation in BNs/02_Maximum_Likelihood_Estimation_for_Bayesian_Networks_15-49.txt 11KB
  252. Lectures/Week 1 - 04 ML-class Octave Tutorial/06_Vectorization_13-48.txt 11KB
  253. Lectures/Week 3 - 09 Inference-Belief Propagation Part 1/02_Properties_of_Cluster_Graphs_15-00.txt 11KB
  254. Lectures/Week 1 - 04 ML-class Octave Tutorial/01_Basic_Operations_13-59.txt 11KB
  255. Lectures/Week 1 - 04 ML-class Octave Tutorial/04_Plotting_Data_09-38.srt 11KB
  256. Lectures/Week 3 - 08 Inference-Variable Elimination/02_Overview-_MAP_Inference_09-42.srt 11KB
  257. Lectures/Week 6 - 14 Inference- Temporal Models and Wrap-up/02_Inference-_Summary_12-45.txt 11KB
  258. Lectures/Week 1 - 02 Bayesian Network Fundamentals/06_Naive_Bayes_09-52.srt 11KB
  259. Lectures/Week 2 - 06 Markov Network Fundamentals/02_General_Gibbs_Distribution_15-52.txt 11KB
  260. Lectures/Week 4 - 10 Inference-Belief Propagation Part 2/03_Clique_Tree_Algorithm_-_Computation_16-18.txt 11KB
  261. Lectures/Week 6 - 16 ML-class Revision/04_Model_Selection_and_Train_Validation_Test_Sets_12-03.txt 11KB
  262. Lectures/Week 1 - 04 ML-class Octave Tutorial/03_Computing_On_Data_13-15.txt 11KB
  263. Lectures/Week 7 - 19 Learning- Parameter Estimation in MNs/02_Maximum_Likelihood_for_Conditional_Random_Fields_13-24.txt 11KB
  264. Lectures/Week 7 - 18 Learning- Parameter Estimation in BNs/01_Maximum_Likelihood_Estimation_14-59.txt 11KB
  265. Lectures/Week 1 - 02 Bayesian Network Fundamentals/03_Flow_of_Probabilistic_Influence_14-36.txt 11KB
  266. Lectures/Week 4 - 10 Inference-Belief Propagation Part 2/01_Properties_of_Belief_Propagation_9-31.srt 10KB
  267. Lectures/Week 6 - 16 ML-class Revision/05_Diagnosing_Bias_vs_Variance_07-42.srt 10KB
  268. Lectures/Week 1 - 04 ML-class Octave Tutorial/05_Control_Statements-_for_while_if_statements_12-55.txt 10KB
  269. Lectures/Week 9 - 21 Learning With Incomplete Data/04_EM_in_Practice_11-17.txt 10KB
  270. Lectures/Week 1 - 03 Template Models/03_Temporal_Models_-_HMMs_12-01.txt 10KB
  271. Lectures/Week 7 - 18 Learning- Parameter Estimation in BNs/04_Bayesian_Prediction_13-40.txt 10KB
  272. Lectures/Week 1 - 02 Bayesian Network Fundamentals/04_Conditional_Independence_12-38.txt 10KB
  273. Assignments/Assignment 2/sendToSamiamGeneCopy.m 10KB
  274. Lectures/Week 6 - 16 ML-class Revision/06_Regularization_and_Bias_Variance_11-20.txt 10KB
  275. Lectures/Week 3 - 08 Inference-Variable Elimination/05_Graph-Based_Perspective_on_Variable_Elimination_15-25.txt 10KB
  276. Lectures/Week 1 - 01 Introduction and Overview/01_Welcome_05-35.srt 10KB
  277. Lectures/Week 2 - 05 Structured CPDs/01_Overview-_Structured_CPDs_08-00.srt 10KB
  278. Lectures/Week 2 - 05 Structured CPDs/04_Continuous_Variables_13-25.txt 10KB
  279. Lectures/Week 3 - 08 Inference-Variable Elimination/06_Finding_Elimination_Orderings_11-58.txt 10KB
  280. Lectures/Week 8 - 20 Structure Learning/05_Learning_Tree_Structured_Networks_12-05.txt 10KB
  281. Lectures/Week 2 - 05 Structured CPDs/03_Independence_of_Causal_Influence_13-08.txt 10KB
  282. Lectures/Week 8 - 20 Structure Learning/03_BIC_and_Asymptotic_Consistency_11-26.txt 9KB
  283. Lectures/Week 2 - 06 Markov Network Fundamentals/01_Pairwise_Markov_Networks_10-59.txt 9KB
  284. Lectures/Week 6 - 16 ML-class Revision/03_Evaluating_a_Hypothesis_07-35.srt 9KB
  285. Lectures/Week 2 - 06 Markov Network Fundamentals/07_Shared_Features_in_Log-Linear_Models_08-28.srt 9KB
  286. Lectures/Week 9 - 21 Learning With Incomplete Data/03_Analysis_of_EM_Algorithm_11-32.txt 9KB
  287. Lectures/Week 3 - 08 Inference-Variable Elimination/04_Complexity_of_Variable_Elimination_12-48.txt 9KB
  288. Lectures/Week 6 - 16 ML-class Revision/01_Regularization-_The_Problem_of_Overfitting_09-42.txt 9KB
  289. Lectures/Week 1 - 03 Template Models/01_Overview_of_Template_Models_10-55.txt 9KB
  290. Lectures/Week 6 - 16 ML-class Revision/02_Regularization-_Cost_Function_10-10.txt 9KB
  291. Assignments/Assignment 7/Part2LogZTest.mat 9KB
  292. Lectures/Week 1 - 01 Introduction and Overview/04_Factors_06-40.srt 8KB
  293. Lectures/Week 7 - 19 Learning- Parameter Estimation in MNs/03_MAP_Estimation_for_MRFs_and_CRFs_9-59.txt 8KB
  294. Lectures/Week 1 - 02 Bayesian Network Fundamentals/07_Application_-_Medical_Diagnosis_09-19.txt 8KB
  295. Lectures/Week 1 - 02 Bayesian Network Fundamentals/02_Reasoning_Patterns_09-59.txt 8KB
  296. Lectures/Week 8 - 20 Structure Learning/01_Structure_Learning_Overview_5-49.srt 8KB
  297. Assignments/Assignment 5/submit_input.mat 8KB
  298. Lectures/Week 1 - 04 ML-class Octave Tutorial/04_Plotting_Data_09-38.txt 8KB
  299. Lectures/Week 3 - 08 Inference-Variable Elimination/02_Overview-_MAP_Inference_09-42.txt 8KB
  300. Lectures/Week 1 - 02 Bayesian Network Fundamentals/06_Naive_Bayes_09-52.txt 8KB
  301. Assignments/Assignment 2/sendToSamiam.m 7KB
  302. Assignments/Assignment 7/Part2FullDataset.mat 7KB
  303. Lectures/Week 4 - 10 Inference-Belief Propagation Part 2/01_Properties_of_Belief_Propagation_9-31.txt 7KB
  304. Lectures/Week 6 - 16 ML-class Revision/05_Diagnosing_Bias_vs_Variance_07-42.txt 7KB
  305. Lectures/Week 1 - 01 Introduction and Overview/03_Distributions_04-56.srt 7KB
  306. Lectures/Week 2 - 05 Structured CPDs/01_Overview-_Structured_CPDs_08-00.txt 7KB
  307. Assignments/Assignment 1/FactorTutorial.m 6KB
  308. Lectures/Week 6 - 16 ML-class Revision/03_Evaluating_a_Hypothesis_07-35.txt 6KB
  309. Lectures/Week 2 - 06 Markov Network Fundamentals/07_Shared_Features_in_Log-Linear_Models_08-28.txt 6KB
  310. Lectures/Week 1 - 01 Introduction and Overview/01_Welcome_05-35.txt 6KB
  311. Lectures/Week 1 - 01 Introduction and Overview/04_Factors_06-40.txt 6KB
  312. Lectures/Week 2 - 06 Markov Network Fundamentals/04_Independencies_in_Markov_Networks_04-48.srt 5KB
  313. Assignments/Assignment 3/PA3TestCases.mat 5KB
  314. Lectures/Week 8 - 20 Structure Learning/01_Structure_Learning_Overview_5-49.txt 5KB
  315. Assignments/Assignment 5/MCMCInference.m 5KB
  316. Lectures/Week 4 - 11 Inference-MAP Estimation Part 1/02_Finding_a_MAP_Assignment_3-57.srt 5KB
  317. Assignments/Assignment 7/CliqueTreeCalibrate.m 5KB
  318. Assignments/Assignment 6/TestCases.m 5KB
  319. Lectures/Week 1 - 01 Introduction and Overview/03_Distributions_04-56.txt 5KB
  320. Assignments/Assignment 9/EM_HMM.m 5KB
  321. Lectures/Week 1 - 04 ML-class Octave Tutorial/07_Working_on_and_Submitting_Programming_Exercises_03-33.srt 5KB
  322. Assignments/Assignment 1/Credit_net.net 4KB
  323. Assignments/Assignment 2/sampleGeneticNetworks.m 4KB
  324. Assignments/Assignment 2/spinalMuscularAtrophyBayesNet.net 4KB
  325. Assignments/Assignment 7/Train2X.mat 4KB
  326. Assignments/Assignment 2/constructDecoupledGeneticNetwork.m 4KB
  327. Assignments/Assignment 7/Train1X.mat 4KB
  328. Assignments/Assignment 5/MHSWTrans.m 4KB
  329. Assignments/Assignment 1/ConvertNetwork.m 4KB
  330. Assignments/Assignment 7/Validation2X.mat 4KB
  331. Assignments/Assignment 7/Validation1X.mat 4KB
  332. Lectures/Week 2 - 06 Markov Network Fundamentals/04_Independencies_in_Markov_Networks_04-48.txt 4KB
  333. Assignments/Assignment 7/ComputeInitialPotentials.m 4KB
  334. Lectures/Week 4 - 11 Inference-MAP Estimation Part 1/02_Finding_a_MAP_Assignment_3-57.txt 4KB
  335. Assignments/Assignment 5/ClusterGraphCalibrate.m 3KB
  336. Assignments/Assignment 3/BuildOCRNetwork.m 3KB
  337. Assignments/Assignment 8/SamplePose.m 3KB
  338. Assignments/Assignment 2/phenotypeGivenCopiesFactor.m 3KB
  339. Assignments/Assignment 9/EM_cluster.m 3KB
  340. Assignments/Assignment 2/genotypeGivenParentsGenotypesFactor.m 3KB
  341. Assignments/Assignment 9/CliqueTreeCalibrate.m 3KB
  342. Lectures/Week 1 - 04 ML-class Octave Tutorial/07_Working_on_and_Submitting_Programming_Exercises_03-33.txt 3KB
  343. Assignments/Assignment 1/submit_input.mat 3KB
  344. Assignments/Assignment 2/genotypeGivenAlleleFreqsFactor.m 3KB
  345. Assignments/Assignment 2/constructGeneticNetwork.m 3KB
  346. Assignments/Assignment 7/InstanceNegLogLikelihood.m 3KB
  347. Assignments/Assignment 8/func_DrawLine.m 3KB
  348. Assignments/Assignment 9/func_DrawLine.m 3KB
  349. Assignments/Assignment 5/BlockLogDistribution.m 3KB
  350. Assignments/Assignment 2/constructSigmoidPhenotypeFactor.m 3KB
  351. Assignments/Assignment 2/childCopyGivenParentalsFactor.m 3KB
  352. Assignments/Assignment 5/VisualizeMCMCMarginals.m 2KB
  353. Assignments/Assignment 7/GenerateAllFeatures.m 2KB
  354. Assignments/Assignment 5/gaimc/scomponents.m 2KB
  355. Assignments/Assignment 9/CreateCliqueTreeHMM.m 2KB
  356. Assignments/Assignment 4/FactorProduct.m 2KB
  357. Assignments/Assignment 5/FactorProduct.m 2KB
  358. Assignments/Assignment 6/FactorProduct.m 2KB
  359. Assignments/Assignment 5/ComputeApproxMarginalsBP.m 2KB
  360. Assignments/Assignment 1/FactorProduct.m 2KB
  361. Assignments/Assignment 6/ObserveEvidence.m 2KB
  362. Assignments/Assignment 2/phenotypeGivenGenotypeMendelianFactor.m 2KB
  363. Assignments/Assignment 5/gaimc/sparse_to_csr.m 2KB
  364. Assignments/Assignment 7/ComputeExactMarginalsBP.m 2KB
  365. Assignments/Assignment 3/ScorePredictions.m 2KB
  366. Assignments/Assignment 4/CreateCliqueTree.m 2KB
  367. Assignments/Assignment 7/FactorSum.m 2KB
  368. Assignments/Assignment 4/ObserveEvidence.m 2KB
  369. Assignments/Assignment 5/ObserveEvidence.m 2KB
  370. Assignments/Assignment 7/FactorProduct.m 2KB
  371. Assignments/Assignment 5/ComputeInitialPotentials.m 2KB
  372. Assignments/Assignment 7/CreateCliqueTree.m 2KB
  373. Assignments/Assignment 8/MaxSpanningTree.m 2KB
  374. Assignments/Assignment 2/phenotypeGivenGenotypeFactor.m 2KB
  375. Assignments/Assignment 2/generateAlleleGenotypeMappers.m 2KB
  376. Assignments/Assignment 1/ObserveEvidence.m 2KB
  377. Assignments/Assignment 5/ConstructRandNetwork.m 2KB
  378. Assignments/Assignment 7/ObserveEvidence.m 2KB
  379. Assignments/Assignment 7/PruneTree.m 2KB
  380. Assignments/Assignment 5/ConstructToyNetwork.m 2KB
  381. Assignments/Assignment 4/CliqueTreeCalibrate.m 2KB
  382. Assignments/Assignment 4/PruneTree.m 2KB
  383. Assignments/Assignment 3/RunInference.m 2KB
  384. Assignments/Assignment 5/FactorMarginalization.m 2KB
  385. Assignments/Assignment 6/FactorMarginalization.m 2KB
  386. Assignments/Assignment 7/GetNextCliques.m 2KB
  387. Assignments/Assignment 4/FactorMaxMarginalization.m 2KB
  388. Assignments/Assignment 7/FactorMaxMarginalization.m 2KB
  389. Assignments/Assignment 4/FactorMarginalization.m 2KB
  390. Assignments/Assignment 5/TestToy.m 2KB
  391. Assignments/Assignment 7/Test1X.mat 2KB
  392. Assignments/Assignment 9/FitLG.m 2KB
  393. Assignments/Assignment 4/ComputeInitialPotentials.m 2KB
  394. Assignments/Assignment 9/ComputeExactMarginalsHMM.m 2KB
  395. Assignments/Assignment 1/FactorMarginalization.m 2KB
  396. Assignments/Assignment 7/FactorMarginalization.m 2KB
  397. Assignments/Assignment 5/CreateClusterGraph.m 2KB
  398. Assignments/Assignment 5/randsample.m 2KB
  399. Assignments/Assignment 6/OptimizeLinearExpectations.m 1KB
  400. Assignments/Assignment 7/LRCostSGD.m 1KB
  401. Assignments/Assignment 7/StochasticGradientDescent.m 1KB
  402. Assignments/Assignment 6/EliminateVar.m 1KB
  403. Assignments/Assignment 9/RecognizeActions.m 1KB
  404. Assignments/Assignment 8/ShowPose.m 1KB
  405. Assignments/Assignment 9/ShowPose.m 1KB
  406. Assignments/Assignment 4/GetNextCliques.m 1KB
  407. Assignments/Assignment 6/VariableElimination.m 1KB
  408. Assignments/Assignment 5/SmartGetNextClusters.m 1KB
  409. Assignments/Assignment 7/LRTrainSGD.m 1KB
  410. Assignments/Assignment 4/EliminateVar.m 1KB
  411. Assignments/Assignment 7/EliminateVar.m 1KB
  412. Assignments/Assignment 8/FitLinearGaussianParameters.m 1KB
  413. Assignments/Assignment 6/OptimizeMEU.m 1KB
  414. Assignments/Assignment 1/ComputeMarginal.m 1KB
  415. Assignments/Assignment 4/ComputeJointDistribution.m 1KB
  416. Assignments/Assignment 3/SerializeFactorsFg.m 1KB
  417. Assignments/Assignment 4/ComputeMarginal.m 1KB
  418. Assignments/Assignment 5/NaiveGetNextClusters.m 1KB
  419. Assignments/Assignment 3/ComputeWordPredictions.m 1KB
  420. Assignments/Assignment 4/SetValueOfAssignment.m 1KB
  421. Assignments/Assignment 6/SetValueOfAssignment.m 1KB
  422. Assignments/Assignment 3/ScoreModel.m 1KB
  423. Assignments/Assignment 5/CheckConvergence.m 1KB
  424. Assignments/Assignment 1/SetValueOfAssignment.m 1KB
  425. Assignments/Assignment 2/SetValueOfAssignment.m 1KB
  426. Assignments/Assignment 5/GetNextClusters.m 1KB
  427. Assignments/Assignment 2/sendToSamiamInfoDecoupled.m 1KB
  428. Assignments/Assignment 1/ComputeJointDistribution.m 1KB
  429. Assignments/Assignment 8/ComputeLogLikelihood.m 1KB
  430. Assignments/Assignment 7/LRSearchLambdaSGD.m 1KB
  431. Assignments/Assignment 5/ExtractMarginalsFromSamples.m 1KB
  432. Assignments/Assignment 6/OptimizeWithJointUtility.m 1KB
  433. Assignments/Assignment 6/SimpleCalcExpectedUtility.m 1KB
  434. Assignments/Assignment 4/ComputeExactMarginalsBP.m 1KB
  435. Assignments/Assignment 3/ComputeTripletFactors.m 1KB
  436. Assignments/Assignment 5/GibbsTrans.m 1018B
  437. Assignments/Assignment 8/LearnCPDsGivenGraph.m 1004B
  438. Assignments/Assignment 7/ComputeConditionedSingletonFeatures.m 998B
  439. Assignments/Assignment 8/LearnGraphAndCPDs.m 974B
  440. Assignments/Assignment 7/ComputeMarginal.m 973B
  441. Assignments/Assignment 3/ComputeSimilarityFactor.m 953B
  442. Assignments/Assignment 6/CalculateExpectedUtilityFactor.m 922B
  443. Assignments/Assignment 3/ComputePairwiseFactors.m 910B
  444. Assignments/Assignment 7/ComputeJointDistribution.m 906B
  445. Assignments/Assignment 6/MultipleUtilityI.mat 898B
  446. Assignments/Assignment 2/sendToSamiamInfo.m 887B
  447. Assignments/Assignment 7/VisualizeCharacters.m 884B
  448. Assignments/Assignment 5/SetValueOfAssignment.m 858B
  449. Assignments/Assignment 3/SetValueOfAssignment.m 856B
  450. Assignments/Assignment 6/FullI.mat 856B
  451. Assignments/Assignment 7/SetValueOfAssignment.m 856B
  452. Assignments/Assignment 6/TestI0.mat 855B
  453. Assignments/Assignment 6/NormalizeCPDFactors.m 845B
  454. Assignments/Assignment 3/ComputeSingletonFactors.m 841B
  455. Assignments/Assignment 4/GetValueOfAssignment.m 838B
  456. Assignments/Assignment 6/GetValueOfAssignment.m 838B
  457. Assignments/Assignment 5/GetValueOfAssignment.m 837B
  458. Assignments/Assignment 3/GetValueOfAssignment.m 835B
  459. Assignments/Assignment 6/SimpleOptimizeMEU.m 835B
  460. Assignments/Assignment 7/GetValueOfAssignment.m 834B
  461. Assignments/Assignment 3/ChooseTopSimilarityFactors.m 832B
  462. Assignments/Assignment 5/randi.m 832B
  463. Assignments/Assignment 1/submitWeb.m 829B
  464. Assignments/Assignment 4/MaxDecoding.m 825B
  465. Assignments/Assignment 9/FactorMarginalization.m 821B
  466. Assignments/Assignment 1/GetValueOfAssignment.m 806B
  467. Assignments/Assignment 2/GetValueOfAssignment.m 805B
  468. Assignments/Assignment 5/MHUniformTrans.m 785B
  469. Assignments/Assignment 6/CPDFromFactor.m 780B
  470. Assignments/Assignment 8/ClassifyDataset.m 751B
  471. Assignments/Assignment 7/ComputeUnconditionedPairFeatures.m 728B
  472. Assignments/Assignment 3/ImageSimilarity.m 708B
  473. Assignments/Assignment 8/LearnGraphStructure.m 708B
  474. Assignments/Assignment 3/ComputeImageFactor.m 696B
  475. Assignments/Assignment 3/VisualizeWord.m 696B
  476. Assignments/Assignment 2/childCopyGivenFreqsFactor.m 686B
  477. Assignments/Assignment 3/ComputeAllSimilarityFactors.m 673B
  478. Assignments/Assignment 7/MaxDecoding.m 659B
  479. Assignments/Assignment 7/LRAccuracy.m 658B
  480. Assignments/Assignment 3/AssignmentToIndex.m 652B
  481. Assignments/Assignment 3/ComputeEqualPairwiseFactors.m 647B
  482. Assignments/Assignment 4/IndexToAssignment.m 641B
  483. Assignments/Assignment 5/IndexToAssignment.m 641B
  484. Assignments/Assignment 6/IndexToAssignment.m 641B
  485. Assignments/Assignment 8/VisualizeModels.m 629B
  486. Assignments/Assignment 4/AssignmentToIndex.m 622B
  487. Assignments/Assignment 4/StandardizeFactors.m 621B
  488. Assignments/Assignment 6/AssignmentToIndex.m 621B
  489. Assignments/Assignment 5/AssignmentToIndex.m 619B
  490. Assignments/Assignment 7/ComputeUnconditionedSingletonFeatures.m 612B
  491. Assignments/Assignment 7/AssignmentToIndex.m 609B
  492. Assignments/Assignment 9/AssignmentToIndex.m 609B
  493. Assignments/Assignment 1/AssignmentToIndex.m 601B
  494. Assignments/Assignment 2/AssignmentToIndex.m 600B
  495. Assignments/Assignment 1/IndexToAssignment.m 599B
  496. Assignments/Assignment 2/IndexToAssignment.m 598B
  497. Assignments/Assignment 7/IndexToAssignment.m 587B
  498. Assignments/Assignment 9/IndexToAssignment.m 587B
  499. Assignments/Assignment 3/IndexToAssignment.m 585B
  500. Assignments/Assignment 5/MHGibbsTrans.m 583B
  501. Assignments/Assignment 1/StandardizeFactors.m 581B
  502. Assignments/Assignment 3/submitWeb.m 581B
  503. Assignments/Assignment 4/submitWeb.m 581B
  504. Assignments/Assignment 6/submitWeb.m 581B
  505. Assignments/Assignment 7/submitWeb.m 580B
  506. Assignments/Assignment 8/submitWeb.m 580B
  507. Assignments/Assignment 9/submitWeb.m 580B
  508. Assignments/Assignment 9/SavePredictions.m 575B
  509. Assignments/Assignment 9/lognormpdf.m 556B
  510. Assignments/Assignment 6/PrintFactor.m 526B
  511. Assignments/Assignment 2/submitWeb.m 523B
  512. Assignments/Assignment 7/LRPredict.m 514B
  513. Assignments/Assignment 8/ConvertAtoG.m 496B
  514. Assignments/Assignment 5/EdgeToFactorCorrespondence.m 482B
  515. Assignments/Assignment 5/rand.m 442B
  516. Assignments/Assignment 8/GaussianMutualInformation.m 442B
  517. Assignments/Assignment 2/sampleFactorListDecoupled.mat 440B
  518. Assignments/Assignment 5/smooth.m 431B
  519. Assignments/Assignment 2/sampleFactorList.mat 396B
  520. Assignments/Assignment 2/computeSigmoid.m 375B
  521. Assignments/Assignment 5/VisualizeToyImageMarginals.m 374B
  522. Assignments/Assignment 9/FitG.m 352B
  523. Assignments/Assignment 5/LogProbOfJointAssignment.m 341B
  524. Assignments/Assignment 9/logsumexp.m 341B
  525. Assignments/Assignment 7/NumParamsForConditionedFeatures.m 321B
  526. Assignments/Assignment 8/VisualizeDataset.m 316B
  527. Assignments/Assignment 8/SampleMultinomial.m 302B
  528. Assignments/Assignment 8/FitGaussianParameters.m 288B
  529. Assignments/Assignment 5/VariableToFactorCorrespondence.m 261B
  530. Assignments/Assignment 9/RecognizeUnknownActions.m 261B
  531. Assignments/Assignment 7/ValidationAccuracy.mat 251B
  532. Assignments/Assignment 9/VisualizeDataset.m 243B
  533. Assignments/Assignment 7/Train1Y.mat 237B
  534. Assignments/Assignment 7/Train2Y.mat 236B
  535. Assignments/Assignment 6/NormalizeFactorValues.m 234B
  536. Assignments/Assignment 8/SampleGaussian.m 232B
  537. Assignments/Assignment 7/NumParamsForUnconditionedFeatures.m 223B
  538. Assignments/Assignment 7/Part1Lambdas.mat 221B
  539. Assignments/Assignment 4/DecodedMarginalsToChars.m 218B
  540. Assignments/Assignment 7/EmptyFeatureStruct.m 195B
  541. Assignments/Assignment 7/Validation1Y.mat 191B
  542. Assignments/Assignment 7/Validation2Y.mat 191B
  543. Assignments/Assignment 7/EmptyFactorStruct.m 183B
  544. Assignments/Assignment 7/Test1Y.mat 182B
  545. Assignments/Assignment 8/lognormpdf.m 159B
  546. Assignments/Assignment 7/sigmoid.m 158B
  547. Assignments/Assignment 9/YourMethod.txt 65B