Generative Adversarial Networks

Recently I have been drawn to generative models, such as LDA (latent Dirichlet allocation) and other topic models.┬áIn deep learning, there are a few examples, such as FVBN (fully visible belief networks), VAE (variational autoencoder), RBM (restricted Boltzmann machine) etc. Recently I have been reading about GAN (generative adversarial networks), first published by Ian Goodfellow … More Generative Adversarial Networks

Tensor Networks and Density Matrix Renormalization Group

A while ago, Mehta and Schwab drew a connection between Restricted Boltzmann Machine (RBM), a type of deep learning algorithm, and renormalization group (RG), a theoretical tool in physics applied on critical phenomena. [Mehta & Schwab, 2014; see previous entry] Can RG be able to relate to other deep leaning algorithms? Schwab wrote a paper … More Tensor Networks and Density Matrix Renormalization Group

Sammon Embedding

Word embedding has been a frequent theme of this blog. But the original embedding has been algorithms that perform a non-linear mapping of higher dimensional data to the lower one. This entry I will talk about one of the most oldest and widely used one: Sammon Embedding, published in 1969. This is an embedding algorithm … More Sammon Embedding

Linking Fundamental Physics to Deep Learning

Ever since Mehta and Schwab laid out the relationship between restricted Boltzmann machines (RBM) and deep learning mathematically (see my previous entry), scientists have been discussing why deep learning works so well. Recently, Henry Lin and Max Tegmark put a preprint on arXiv (arXiv:1609.09225), arguing that deep learning works because it captures a few essential … More Linking Fundamental Physics to Deep Learning

SOCcer: Computerized Coding In Epidemiology

There are many tasks that involve coding, for example, putting kids into groups according to their age, labeling the webpages about their kinds, or putting students in Hogwarts into four colleges… And researchers or lawyers need to code people, according to their filled-in information, into occupations. Melissa Friesen, an investigator in Division of Cancer Epidemiology … More SOCcer: Computerized Coding In Epidemiology