David Refaeli MaverickMeerkat

## sbi-code-example.ipynb

      
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              September 10, 2022 09:11
            
              
                SBI Code Example.ipynb
              
          
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## Gauss-Newton.ipynb

      
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              September 11, 2022 14:09
            
          
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## Gaussian Processes.ipynb

      
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                / Gaussian Processes.ipynb
            
            
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              September 11, 2022 14:45
            
          
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## gpreg-vs-multiple-linear-regression-portfolio.ipynb

      
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                MaverickMeerkat
                / gpreg-vs-multiple-linear-regression-portfolio.ipynb
            
            
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              March 10, 2023 11:18
            
              
                GPReg vs. (Multiple) Linear Regression - portfolio.ipynb
              
          
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## implement-a-nn-part-3-multiclass-using-softmax.ipynb

      
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                / implement-a-nn-part-3-multiclass-using-softmax.ipynb
            
            
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              April 4, 2023 13:04
            
              
                Implement a NN - Part 3: Multiclass using Softmax.ipynb
              
          
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## implement-a-nn-part-5-batch-norm.ipynb

      
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                MaverickMeerkat
                / implement-a-nn-part-5-batch-norm.ipynb
            
            
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              April 4, 2023 15:42
            
              
                Implement a NN - Part 5: Batch Norm.ipynb
              
          
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## sgd-variants-momentum-rmsprop-adam-part-2-code.ipynb

      
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                / sgd-variants-momentum-rmsprop-adam-part-2-code.ipynb
            
            
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              April 4, 2023 16:04
            
              
                SGD Variants: Momentum, RMSprop, Adam - Part 2: Code.ipynb
              
          
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## KDE_Kernel_Regression_1.R
library(gganimate)
library(plotly)

###########
# General #
###########
# Set the Kenrel function
# Uniform Kernel
f = function(u) as.numeric((u<=0.5) & (u>=-0.5))
# Normal Kernel

## EM_GMM.R
# Expectation Maximization - Gaussian Mixture Model

library(ks)         # for kde
library(mvtnorm)    # for MVNormal
library(extraDistr) # for Categorical & Dirichlet distribution
library(ggplot2)    # for plotting
library(pracma)     # for sqrtm

######################
#  1D, 2-components  #

## CAVI_Bayes_GMM.R
# Using the CAVI algorithm on a (Bayesian) GMM example

library(mvtnorm)    # for multivariate normal density
library(extraDistr) # for Categorical distribution
library(pracma)     # for 2d-integral, sqrtm
library(matlib)     # for solving linear equations
library(ggplot2)    # for plotting

# Hyper Parameters
sigma = 3   # Variance of mu
	library(gganimate)
	library(plotly)

	###########
	# General #
	###########
	# Set the Kenrel function
	# Uniform Kernel
	f = function(u) as.numeric((u<=0.5) & (u>=-0.5))
	# Normal Kernel
	# Expectation Maximization - Gaussian Mixture Model

	library(ks) # for kde
	library(mvtnorm) # for MVNormal
	library(extraDistr) # for Categorical & Dirichlet distribution
	library(ggplot2) # for plotting
	library(pracma) # for sqrtm

	######################
	# 1D, 2-components #
	# Using the CAVI algorithm on a (Bayesian) GMM example

	library(mvtnorm) # for multivariate normal density
	library(extraDistr) # for Categorical distribution
	library(pracma) # for 2d-integral, sqrtm
	library(matlib) # for solving linear equations
	library(ggplot2) # for plotting

	# Hyper Parameters
	sigma = 3 # Variance of mu