Moved to WordPress!

Always looking for a better publishing solution!


I wanted to temporarily go without a personal server and this turned out to be one of the best solutions. To setup webpages with LaTeX render in HTML requires some struggle (not hard, but I am too lazy right now.) I am seriously considering KaTeX + other webpage packages to fire up a highly personalized site some time soon, but more on that later.

Let’s try this:

p(x \mid y) = \frac{p(x, y)}{p(y)}

It works!

Couple of topics to be discussed here soon (details, order and time-schedule TBD):

  • Gumbel softmax trick / Concrete distribution
  • Hamiltonian Monte Carlo (HMC, NUTS, stochastic gradient HMC)
  • Variational inference (VI, SVI, BBVI, ADVI, RSVI, OPVI, VGP, Hamiltonian VI, etc.)
  • Generative adversarial networks (GAN, InfoGAN, Conditional GAN, Wasserstein GAN, DCGAN, ALI, BiGAN, LS-GAN, etc.)
  • Causal inference (potential outcomes, SUTVA, instrumental variables, propensity scores, causal graphs, Bayesian, etc.)
  • Expectation maximization (EM, stochastic EM, Monte Carlo EM, etc.)
  • Attention models (DRAW, One-shot)
  • Recurrent neural nets (RNN, LSTM, GRU)
  • Resampling methods (parametric bootstrap, nonparametric bootstrap, jackknife estimator)
  • Tensor probabilistic models (Tucker decomposition, HOSVD, Parafac)
  • Sequential Monte Carlo
  • Nonparametric Bayesian models (CRP, HDP, IBP, GP, stick breaking construction, complete random measures, etc.)
  • Variational autoencoders (VAE, SVAE)
  • Proximal gradient methods
  • Reinforcement learning (model-based, model-free, Q learning, Monte Carlo tree search, TD-\lambda, SARSA, etc.)
  • Dimensionality reduction (PCA, robust PCA, probabilistic PCA, ICA, etc.)
  • Linear regression
  • Logistic regression
  • ML/Statistics tricks