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""" Deep Auto-Encoder implementation | |
An auto-encoder works as follows: | |
Data of dimension k is reduced to a lower dimension j using a matrix multiplication: | |
softmax(W*x + b) = x' | |
where W is matrix from R^k --> R^j | |
A reconstruction matrix W' maps back from R^j --> R^k |
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import tensorflow as tf | |
import numpy as np | |
import math | |
#import pandas as pd | |
#import sys | |
input = np.array([[2.0, 1.0, 1.0, 2.0], | |
[-2.0, 1.0, -1.0, 2.0], | |
[0.0, 1.0, 0.0, 2.0], | |
[0.0, -1.0, 0.0, -2.0], |
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