Topic: "contrastive-divergence-algorithm"
yell/boltzmann-machines
Boltzmann Machines in TensorFlow with examples
Language: Jupyter Notebook - Size: 354 MB - Last synced at: 22 days ago - Pushed at: over 3 years ago - Stars: 848 - Forks: 136
Shikhargupta/Spiking-Restricted-Boltzmann-Machine
RBM implemented with spiking neurons in Python. Contrastive Divergence used to train the network.
Language: Python - Size: 4.21 MB - Last synced at: over 1 year ago - Pushed at: over 7 years ago - Stars: 26 - Forks: 10
mark-antal-csizmadia/rbm_dbn
Restricted Boltzmann Machines (RBMs) and Deep Belief Networks (DBNs) from scratch for representation learning on the MNIST dataset.
Language: Jupyter Notebook - Size: 108 MB - Last synced at: over 2 years ago - Pushed at: almost 4 years ago - Stars: 1 - Forks: 1
isabekov/GBPRBM_NumPy
A Python3-NumPy implementation of contrastive divergence algorithm for training Gaussian-Bipolar Restricted Boltzmann Machines
Language: Python - Size: 285 KB - Last synced at: about 2 years ago - Pushed at: almost 8 years ago - Stars: 1 - Forks: 1
dkomni/machine-learning-overview
Machine Learning Basics: Artificial Neural Networks, Generative Modeling, Boltzmann Machines, GANs
Language: Jupyter Notebook - Size: 2.49 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0
bhavanajain/RBMs
In summer 2017, I was an intern at the Purdue University working under Prof Bruno Ribeiro on improving the training of Restricted Boltzmann Machines. We used the Las Vegas transformation of Markov Chain Monte Carlo method to obtain better samples to estimate the negative phase of the gradient. The model trained via this method achieved a significantly higher likelihood on the MNIST data as compared to the conventional model trained via Contrastive Divergence. This repository contains a brief report on my work.
Size: 325 KB - Last synced at: about 2 years ago - Pushed at: over 7 years ago - Stars: 0 - Forks: 0
