Max-Heinrich Laves mlaves

## bayesian_optimization.ipynb

      
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              January 23, 2021 12:50
            
              
                bayesian_optimization.ipynb
              
          
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## two_moons_create_opener.ipynb

      
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              April 2, 2025 08:20
            
              
                Unsupervised toy experiment on the "two moons" data set.
              
          
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## linear-regression-metropolis-hastings.ipynb

      
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              September 17, 2020 14:18
            
              
                Linear Regression Metropolis-Hastings.ipynb
              
          
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## pyro_classification.ipynb

      
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              August 8, 2024 10:32
            
              
                Simple Classification Example in Pyro with SVI and MCMC
              
          
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## fast_multidim_dot_numpy.ipynb

      
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                / fast_multidim_dot_numpy.ipynb
            
            
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              September 6, 2019 09:09
            
              
                fast_multidim_dot_numpy.ipynb
              
          
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## Newton-Raphson-Clojure.clj
(def step 1E-10)
(def eps 1E-15)

(defn rootNP
  [f x]
  (let [m (/ (- (f (+ x step)) (f x)) step)
        b (- (f x) (* m x))
        x-0 (- (/ b m))]
    (if (<= (Math/abs (- x x-0)) eps)
      x-0

## Newton-Raphson-Python.py
import time
import numpy as np

def rootNR(f, start_x):
    step = 1e-10 # small increment
    x = start_x
    eps = 1e-15 # need eps, on some functions abs(x-x_0) never reaches zero

    while True:
        m = (f(x+step) - f(x))/step
	(def step 1E-10)
	(def eps 1E-15)

	(defn rootNP
	[f x]
	(let [m (/ (- (f (+ x step)) (f x)) step)
	b (- (f x) (* m x))
	x-0 (- (/ b m))]
	(if (<= (Math/abs (- x x-0)) eps)
	x-0
	import time
	import numpy as np

	def rootNR(f, start_x):
	step = 1e-10 # small increment
	x = start_x
	eps = 1e-15 # need eps, on some functions abs(x-x_0) never reaches zero

	while True:
	m = (f(x+step) - f(x))/step