Simeon Carstens simeoncarstens

## emacs-pkg-install.sh
#!/bin/bash
#
# I wrapped the code constructed in
#
# http://hacks-galore.org/aleix/blog/archives/2013/01/08/install-emacs-packages-from-command-line
#
# in a single bash script, so I would a single code snippet.
#

# Package to be installed

## likelihood_gradient.ipynb

      
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                simeoncarstens
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              April 18, 2020 20:17
            
          
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## smc.ipynb

      
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                simeoncarstens
                / smc.ipynb
            
            
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              January 27, 2020 14:21
            
              
                Importance Sampling, Sequential Monte Carlo, Particle Filtering and stuff
              
          
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## binf.ipynb

      
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                simeoncarstens
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              July 18, 2019 12:39
            
              
                My personal solution for probabilistic programming: binf
              
          
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## analytical_hmc.py
from numpy import sin, cos, arctan, sqrt, exp, random, pi, linspace
import matplotlib.pyplot as plt

def draw_sample(xold, sigma):

    t = 3.0
    vold = random.normal()
    phi = arctan(-vold / xold * sigma)
    A = vold * sigma * sqrt(xold ** 2 / sigma ** 2 / vold ** 2 + 1)
    xnew = A * cos(t / sigma + phi)
	#!/bin/bash
	#
	# I wrapped the code constructed in
	#
	# http://hacks-galore.org/aleix/blog/archives/2013/01/08/install-emacs-packages-from-command-line
	#
	# in a single bash script, so I would a single code snippet.
	#

	# Package to be installed
	from numpy import sin, cos, arctan, sqrt, exp, random, pi, linspace
	import matplotlib.pyplot as plt

	def draw_sample(xold, sigma):

	t = 3.0
	vold = random.normal()
	phi = arctan(-vold / xold * sigma)
	A = vold * sigma * sqrt(xold 2 / sigma 2 / vold ** 2 + 1)
	xnew = A * cos(t / sigma + phi)