Unsupervised Feature Learning via Non-parametric Instance Discrimination
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Updated
Mar 25, 2021 - Python
Unsupervised Feature Learning via Non-parametric Instance Discrimination
The Noise Contrastive Estimation for softmax output written in Pytorch
Tensorflow implementation of "Representation Learning with Contrastive Predictive Coding"
Re-implementation of the Noise Contrastive Estimation algorithm for pyTorch, following "Noise-contrastive estimation: A new estimation principle for unnormalized statistical models." (Gutmann and Hyvarinen, AISTATS 2010)
Tensorflow NCE loss in Keras
Noise Contrastive Estimation (NCE) in PyTorch
Flow Contrastive Estimation (FCE) PyTorch Implementation on 2D data
a pytorch version lstm language model
InfoNCE, Soft Nearest Neighbour on MNIST and Fashion-MNIST
Compute package engines constraint to the most restrictive range version used by your dependencies.
Evaluated the word vectors learned from both nce and cross entropy loss functions using word analogy tests
A comprehensive ist of all courses I have taken and successfully completed in University π, Coursera π, Udemy etc.
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