Scripts I wrote during my master

• For the probabilistic graphical models course (F. bach)

  • K-Means (Done)
  • Gaussian Mixture Model (just to commit)
  • Hidden Markov Chain (Done)
  • Conditional Random Fields (TODO)

• For the computer vision & object recognition course (J. Sivic, J. Ponce, C. Schmid)

  • Project: multiview CCA for caption generation using CNN (ImageNet pretrained) and Word2Vec embedding (TODO)

• For random matrices course (TODO)

• Semi-circle law

• Marcenko Pastur distribution and first order perturbation

• TP1 (eigein values of large covariance matrices estimation)

• TP2 (spectral clustering)

• For the stochastic image analysis course (A. Desolneux)

• n-grams for text generation

• binary image segmentation via MRFs (simulated annealing/MCMC for inference)

• For the kernel methods course (J. Mairal)

• code of our SVM (ranked 4th on the kaggle)