$$ \newcommand{\dint}{\mathrm{d}} \newcommand{\vphi}{\boldsymbol{\phi}} \newcommand{\vpi}{\boldsymbol{\pi}} \newcommand{\vpsi}{\boldsymbol{\psi}} \newcommand{\vomg}{\boldsymbol{\omega}} \newcommand{\vsigma}{\boldsymbol{\sigma}} \newcommand{\vzeta}{\boldsymbol{\zeta}} \renewcommand{\vx}{\mathbf{x}} \renewcommand{\vy}{\mathbf{y}} \renewcommand{\vz}{\mathbf{z}} \renewcommand{\vh}{\mathbf{h}} \renewcommand{\b}{\mathbf} \renewcommand{\vec}{\mathrm{vec}} \newcommand{\vecemph}{\mathrm{vec}} \newcommand{\mvn}{\mathcal{MN}} \newcommand{\G}{\mathcal{G}} \newcommand{\M}{\mathcal{M}} \newcommand{\N}{\mathcal{N}} \newcommand{\S}{\mathcal{S}} \newcommand{\I}{\mathcal{I}} \newcommand{\diag}[1]{\mathrm{diag}(#1)} \newcommand{\diagemph}[1]{\mathrm{diag}(#1)} \newcommand{\tr}[1]{\text{tr}(#1)} \renewcommand{\C}{\mathbb{C}} \renewcommand{\R}{\mathbb{R}} \renewcommand{\E}{\mathbb{E}} \newcommand{\D}{\mathcal{D}} \newcommand{\inner}[1]{\langle #1 \rangle} \newcommand{\innerbig}[1]{\left \langle #1 \right \rangle} \newcommand{\abs}[1]{\lvert #1 \rvert} \newcommand{\norm}[1]{\lVert #1 \rVert} \newcommand{\two}{\mathrm{II}} \newcommand{\GL}{\mathrm{GL}} \newcommand{\Id}{\mathrm{Id}} \newcommand{\grad}[1]{\mathrm{grad} \, #1} \newcommand{\gradat}[2]{\mathrm{grad} \, #1 \, \vert_{#2}} \newcommand{\Hess}[1]{\mathrm{Hess} \, #1} \newcommand{\T}{\text{T}} \newcommand{\dim}[1]{\mathrm{dim} \, #1} \newcommand{\partder}[2]{\frac{\partial #1}{\partial #2}} \newcommand{\rank}[1]{\mathrm{rank} \, #1} \newcommand{\inv}1 \newcommand{\map}{\text{MAP}} \newcommand{\L}{\mathcal{L}} \DeclareMathOperator*{\argmax}{arg\,max} \DeclareMathOperator*{\argmin}{arg\,min} $$

Minkowski's, Dirichlet's, and Two Squares Theorem

Application of Minkowski's Theorem in geometry problems, Dirichlet's Approximation Theorem, and Two Squares Theorem.

Reduced Betti number of sphere: Mayer-Vietoris Theorem

A proof of reduced homology of sphere with Mayer-Vietoris sequence.

Brouwer's Fixed Point Theorem: A Proof with Reduced Homology

A proof of special case (ball) of Brouwer's Fixed Point Theorem with Reduced Homology.

Natural Gradient Descent

Intuition and derivation of natural gradient descent.

Fisher Information Matrix

An introduction and intuition of Fisher Information Matrix.

Introduction to Annealed Importance Sampling

An introduction and implementation of Annealed Importance Sampling (AIS).

Gibbs Sampler for LDA

Implementation of Gibbs Sampler for the inference of Latent Dirichlet Allocation (LDA)

Boundary Seeking GAN

Training GAN by moving the generated samples to the decision boundary.

Least Squares GAN

2017 is the year GAN loss its logarithm. First, it was Wasserstein GAN, and now, it's LSGAN's turn.

CoGAN: Learning joint distribution with GAN

Original GAN and Conditional GAN are for learning marginal and conditional distribution of data respectively. But how can we extend them to learn joint distribution instead?