Implementation of G. E. Hinton and R. R. Salakhutdinov's Reducing the Dimensionality of Data with Neural Networks (Tensorflow)
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Updated
Apr 28, 2024 - Python
Implementation of G. E. Hinton and R. R. Salakhutdinov's Reducing the Dimensionality of Data with Neural Networks (Tensorflow)
Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
A Python-implemented RBM project exploring generative learning through the classification of the Iris dataset, featuring a user-friendly GUI and advanced data handling capabilities.
A small collection of ANN models built while completing a Udemy course on deep learning.
Neural Network Many-Body Wavefunction Reconstruction
Deep Belief Networks in Tensorflow 2
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 net…
Keras framework for unsupervised learning
A user-friendly web application built with Streamlit that offers personalized movie recommendations based on user ratings using a baseline predictive model and RBM neural network
Practical works on Bayesian classification, Hidden Markov Models and Restricted Boltzmann Machines
Energy Based Models in PyTorch
Demonstration of the mini-lab (practical) component activities conducted for the course of Neural Networks and Deep Learning (19CSE456).
code & assignments from Laboratory of Computational Physics (module B) held at University of Padova by Prof. Marco Baiesi during Academic Year 2022-2023
Restricted Boltzmann Machine (classification on MNIST)
Machine Learning Basics: Artificial Neural Networks, Generative Modeling, Boltzmann Machines, GANs
Learning a few historical techniques for machine learning for a class at UIUC: Gibbs sampling, Hopfield networks, restricted boltzmann machines
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.
Inteligencia Artificial - Maquinas de Boltzmann Restringidas
projects of all sorts of neural network
This repository is for the Movie Recommendation System developed using the Restricted Boltzmann Machine Algorithm
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