Statistics

(Pytorch) 06.Variational Auto Encoder

4 minute read

Auto Encoding Variational Bayes (2014)

Uncertainty

1 minute read

Uncertainty, Aleatoric, Epsitemic, OoD

Normalizing Flow

1 minute read

Normalizing Flow, Variational Inference

Gumbel-Softmax Trick

1 minute read

Gumbel-max trick,Gumbel-softmax trick, Reparameterization Trick

Hamiltonian Monte Carlo

2 minute read

HMC

Dirichlet Process

6 minute read

Dirichlet Process ( Dirichlet Distribution,DPMM, HDP)

LDA with Collapsed Gibbs Sampling

3 minute read

LDA with Collapsed Gibbs Sampling

t-SNE

3 minute read

t-distributed Stochastic Neighborhood Embedding

Restricted Boltzmann Machine 코드 (pytorch)

2 minute read

Restricted Boltzmann Machine 2, Movie Recommendation

Restricted Boltzmann Machine 이론

3 minute read

Restricted Boltzmann Machine

Jackknife & Bootstrapping [2]

1 minute read

Replication Variance Estimation

Jackknife & Bootstrapping [1]

2 minute read

Replication Variance Estimation

Factorization Machine

4 minute read

Factorization Machine

(paper) Weights Uncertainty in Neural Networks

6 minute read

Bayes by Backprop

Gaussian Process (2) GP Implementation

1 minute read

GP(2) - GP Implementation

Gaussian Process (1) Gaussian Process Regression

5 minute read

GP(1) - Gaussian Process Regression

Hidden Markov Model

5 minute read

Hidden Markov Model (HMM)

(Deep Bayes) 06.Stochastic V.I and Variational AutoEncoders

7 minute read

Deep Bayes Lecture 06

(Deep Bayes) 05.TEST - Approximate Bayesian Inference

5 minute read

Deep Bayes Lecture 05

(Deep Bayes) 04.EM Algorithm

2 minute read

Deep Bayes Lecture 03

(Deep Bayes) 03.Variational Inference

2 minute read

Deep Bayes Lecture 02

(Deep Bayes) 02.TEST - Bayesian Reasoning

2 minute read

Deep Bayes Lecture 03

(Deep Bayes) 01.Bayesian Framework

4 minute read

Deep Bayes Lecture 01

17.LDA_intro2

1 minute read

LDA Model, E-step & M-step

18.(VI) Variational Inference (2)

3 minute read

Algorithms of Variational EM

17.(VI) Variational Inference

2 minute read

Algorithms of Variational EM

16.(VI) Variational Transform

2 minute read

Algorithms of Variational EM

15.(VI) Variational Inference Intro(2)

less than 1 minute read

Algorithms of Variational EM

14.(VI) Variational Inference Intro(1)

1 minute read

Introduction of Variational Inference

13.(EM algorithm) K-means from EM perspective

1 minute read

K-means, GMM, EM algorithm

12.(EM algorithm) General EM for GMM

less than 1 minute read

E-step & M-step for GMM

11.(EM algorithm) EM algorithm (2)

1 minute read

E-step / M-step

10.(EM algorithm) EM algorithm (1)

2 minute read

Jensen’s Inequality / KL-divergence / EM algorithm example

9.(EM algorithm) Latent Variable Models

4 minute read

Latent Variable / Gaussian Mixture Models

LDA Model

1 minute read

LDA Model, E-step & M-step

LDA_intro

1 minute read

Introduction of Latent Dirichlet Allocation

8.(sampling) Gibbs Sampling

2 minute read

Gibbs Sampling

7.(sampling) Metropolis-Hastings

3 minute read

Markov Chain Monte Carlo / Metropolis-Hastings

6.(sampling) Markov Chain Monte Carlo

1 minute read

Markov Chain Monte Carlo / Metropolis-Hastings

5.(basic) Statistical modeling and Monte Carlo estimation

4 minute read

Objectives of Statistical Models / Bayesian Modeling / Monte Carlo Estimation

4.(basic) Models for Continuous data

5 minute read

Exponential / Normal / Jeffery’s Prior

3.(basic) Priors and Models for Discrete Data

6 minute read

Priors / Bernoulli & Binomial / Poisson

2.(basic) Statistical Inference

3 minute read

Introduction of Frequentists and Bayesian Inference

1.(basic) Probability and Bayes’ Theorem

1 minute read

Bayesian / Frequentists / Bayes’ Theorem

Bayesian Optimization (1)

4 minute read

Bayesian Optimization 이론 설명

Seunghan Lee

Statistics