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66 search results found

Generative Models ⭐ 6,010

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

Esl Cn ⭐ 2,283

The Elements of Statistical Learning (ESL)的中文翻译、代码实现及其习题解答。

Restricted Boltzmann Machines ⭐ 833

Restricted Boltzmann Machines in Python.

NeuPy is a Tensorflow based python library for prototyping and building neural networks

Keras_extensions ⭐ 196

A collection of small extensions to Keras (RBM, momentum schedule, ..)

Sparse Evolutionary Artificial Neural Networks ⭐ 187

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).

Modular Restricted Boltzmann Machine (RBM) implementation using Theano

Neural models for Collaborative Filtering

Char Rbm ⭐ 100

Character-level RBMs for short text

Unsupervised learning and generative models in python/pytorch.

Neural_net_newbies ⭐ 89

Neural Net Starter Examples

Restricted Boltzmann Machines

Music_rnn_rbm ⭐ 81

Generating longer musical pieces with an RNN-RBM in TensorFlow

Rbm Ae Tf ⭐ 79

Tensorflow 1.X implementation of Restricted Boltzman Machine(RBM) and Autoencoder with layerwise pretraining.

Pytorch Rbm ⭐ 76

Restricted Boltzmann Machines (RBMs) in PyTorch

Deeplearningbenchmarks ⭐ 75

Mnist Challenge ⭐ 64

My solution to TUM's Machine Learning MNIST challenge 2016-2017 [winner]

Learnergy ⭐ 62

💡 Learnergy is a Python library for energy-based machine learning models.

Variational Recurrent Autoencoder ⭐ 55

Implementation of the VRAE

Parametric T Sne In Keras ⭐ 52

a python implementation of Parametric t-SNE in Keras

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

PyDeep is a machine learning / deep learning library with focus on unsupervised learning. The library has a modular design, is well documented and purely written in Python/Numpy. This allows you to understand, use, modify, and debug the code easily. Furthermore, its extensive use of unittests assures a high level of reliability and correctness.

Coursera Neural Net ⭐ 42

Assignments for Geoffrey Hinton's Neural Net Course on Coursera, translated from (gross)Matlab into (beautiful)Python.

Deep Belief Networks In Pytorch ⭐ 38

The aim of this repository is to create RBMs, EBMs and DBNs in generalized manner, so as to allow modification and variation in model types.

CFRBM is a implementation of the RBM model to the collaborative filtering task

Keras_bn_library ⭐ 31

keras extended library

Book Recommender System Rbm ⭐ 28

A book recommender system created using simple Restricted Boltzmann Machines in TensorFlow

Train an Infinite Restricted Boltzmann Machine

Probabilistic Graphical Models in Python3.

Simple code tutorial for deep belief network (DBN)

Spiking Restricted Boltzmann Machine ⭐ 17

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

Deep Learning Models ⭐ 16

Deep Learning Models implemented in python.

Movie Recommender Using Rbm ⭐ 16

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

Machinelearning ⭐ 16

A collection of Python code and machine learning exercises

Event-Driven CD in Spiking Neural Networks

Chalearn2014_wudi_lio ⭐ 15

My restricted boltzmann machine demo

Hands-on in-person workshop for Deep Learning with TensorFlow

Restricted Boltzmann Machine implementation in Python for pre-training deep neural networks

Simple demo of logic used in https://arxiv.org/abs/1712.05304 [outdated]

Movie Reco Using Rbm ⭐ 13

Movie Recommendation using Restricted Boltzmann Machine (RBM)

Cdl_rbm_tutorial ⭐ 11

Tutorial on machine learning many-body physics with Boltzmann machines

Rbm Tensorflow ⭐ 11

Tensorflow Implementation of RBM

code for experiments in Grosse and Salakhutdinov, 2015.

Tensorflow Implementation Of Dbn Including Gbrbm Bbrbm ⭐ 11

The application of RBM using tensorflow. Including DBN and mult-type RBM (GBRBM, BBRBM)

Neural Variational Inference ⭐ 11

Neural variational inference and learning in undirected graphical models http://www.stanford.edu/~kuleshov/papers/nips2017.

SClean is a tool for data cleaning and visualization of the output of various packages in the sysstat tool under Linux.

Music Generator ⭐ 10

Experimentation with learning cross-modal mappings (video to audio) as an approach to music generation

Convolutional Restricted Boltzmann Machine

Rbm Dbn Theano Dl4j ⭐ 9

Train a DBN to classify a set of test data similar to MNIST, Using DL4J & theano (Project of Pattern Recognition course)

Neural Network Quantum State ⭐ 9

Python Dbn ⭐ 8

Learning about RBMs and DBNs

Music Generator ⭐ 8

Generates music by learning from midi files. Training is done using Restricted Boltzmann Machines in TensorFlow

Regularized Rbm ⭐ 7

A regularized version of RBM for unsupervised feature selection.

Android Malware Detection ⭐ 7

Android Malware detection using Deep Learning Hybrid Model.

Harmonium ⭐ 6

Simple Restricted Boltzmann Machine implementation with TensorFlow.

Rnn Rbm In Theano ⭐ 6

An implementation of RNN-RBM & GBRBM.

Graduation Project ⭐ 6

Code for experiments with convolutional classification restricted Boltzmann machines

Medcodelearn ⭐ 5

Playground for machine learning with medical coding data and medical classifications

My python implementation of RBM and denoising Autoencoder for pre-training

Rbm Smple ⭐ 5

Simple working implementation of Restricted Boltzmann Machines learning algorithm in Python using numpy. Works on MNIST dataset.

Python Machine Learning Models ⭐ 5

Barebones Python implementations of machine learning models, without using machine learning libraries

Bethe Min ⭐ 5

Rbm_based_autoencoders_with_tensorflow ⭐ 5

Mnist Rbm ⭐ 5

A spiking-neuron version of an RBM trained on the MNIST dataset

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