The deeplearning algorithms implemented by tensorflow

Simple framework for image and video deblurring, implemented by PyTorch

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

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.

GPU accelerated Deep Belief Network

Experimenting with RBMs using scikit-learn on MNIST and simulating a DBN using Keras.

https://github.com/mehulrastogi/Deep-Belief-Network-pytorch

DBN Data Structures and Algorithms in C for Dynamic Bayesian Networks

Open DRUWA - Open Deep Realtime User Welcoming Assistant

Nebula: Lightweight Neural Network Benchmarks

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

Classifies images using DBN (Deep Belief Network) algorithm implementation from Accord.NET library

vPaypal provides mobile payment with enhanced security and convenience by using voice recognition and voice control module.The system consists of a mobile app and a server.

The software includes a dynamic bayesian network with genetic feature space selection, includes 5 econometric data.frames with 263 time series.

Interface between a DBN model and CNN models to learn from demonstrations

Daft wrapper for easily creating Dynamic Bayesian Network plots

Tia's implementation of Neural Network Architectures from scratch

📄 Official implementation regarding the chapter "Fine-Tuning Deep Belief Networks with Harmony-Based Optimization".

Simple Keras-inspired DeepLearning Framework implemented in Python with Numpy backend: MLP, CNN, RNN, RBF, SOM, DBN...

A series of 12 assignments/labs regarding Stochastic Processes and Machine Learning including a plethora of models and techniques implemented in Google Colab notebooks