restricted-boltzmann-machine

Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

Boltzmann Machines in TensorFlow with examples

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

Always sparse. Never dense. But never say never. A Sparse Training repository for the Adaptive Sparse Connectivity concept and its algorithmic instantiation, i.e. Sparse Evolutionary Training, to boost Deep Learning scalability on various aspects (e.g. memory and computational time efficiency, representation and generalization power).

Neural Network Many-Body Wavefunction Reconstruction

Restricted Boltzmann Machines (RBMs) in PyTorch

This repository has implementation and tutorial for Deep Belief Network

The goal of this project is to solve the task of name transcription from handwriting images implementing a NN approach.

An implementation of Restricted Boltzmann Machine in Pytorch

Implementation of Restricted Boltzmann Machine (RBM) and its variants in Tensorflow

A Library for Modelling Probabilistic Hierarchical Graphical Models in PyTorch

Simple code tutorial for deep belief network (DBN)

A Julia package for training and evaluating multimodal deep Boltzmann machines

Implementation of G. E. Hinton and R. R. Salakhutdinov's Reducing the Dimensionality of Data with Neural Networks (Tensorflow)

A Movie Recommender System using Restricted Boltzmann Machine (RBM), approach used is collaborative filtering.

RBM implemented with spiking neurons in Python. Contrastive Divergence used to train the network.

algorithm for study: multi-layer-perceptron, cluster-graph, cnn, rnn, restricted boltzmann machine, bayesian network

Pytorch implementation of an autoencoder built from pre-trained Restricted Boltzmann Machines (RBMs)

Fill missing values in Pandas DataFrames using Restricted Boltzmann Machines

Restricted Boltzmann Machines as Keras Layer