There are 3 repositories under dbn topic.
The deeplearning algorithms implemented by tensorflow
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
https://github.com/mehulrastogi/Deep-Belief-Network-pytorch
Open DRUWA - Open Deep Realtime User Welcoming Assistant
DBN++ Data Structures and Algorithms in C++ for Dynamic Bayesian Networks
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
Nebula: Lightweight Neural Network Benchmarks
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.
Interface between a DBN model and CNN models to learn from demonstrations
Daft wrapper for easily creating Dynamic Bayesian Network plots
The software includes a dynamic bayesian network with genetic feature space selection, includes 5 econometric data.frames with 263 time series.
Tia's implementation of Neural Network Architectures from scratch
AI model example
đź“„ 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...
The DBN compiler translates DBN source into SVG source file. The resulting SVG source files can then be loaded and executed on any web browser. (Pet project)
A series of 12 assignments/labs regarding Stochastic Processes and Machine Learning including a plethora of models and techniques implemented in Google Colab notebooks
A version of the learnergy package to deal with video datasets
A simple JavaScript compiler that compiles DBN like language (by MIT) and generates the corresponding shapes in the form of SVGs
An pytorch implementation of Deep Belief Network with sklearn compatibility for classification. The training process consists the pretraining of DBN, fine-tuning as an unrolled autoencoder-decoder, and supervised fine-tuning as a classifier.
Uncover the secrets of deep learning with FashionDBN - implementing PyTorch's Deep Belief Network for accurate image classification and beyond.
This repository is dedicated to my collaboration in the "AUTOMOTIVE" Project. This project's objective is to development automatic face image/video-based drowsiness recognition.
From Markov Fields to Deep Belief Networks theory and experimentation on Google Landmark Recognition.
Utilisation de modèles génératifs comme tâche prétexte pour pré-entrainement de DNN pour classification.
A repository for generating synthetic data (images) using various DL/ML models.
Cognition and Computation Course Project
ECG Classification of Normal and Abnormal with GB-DBN Model (pytorch)
A framework that focuses on using bayesian and Dynamic Bayesian Networks to perform Learning from observation on Discrete Domains