Neural Network Many-Body Wavefunction Reconstruction
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Updated
Jul 28, 2024 - Python
Neural Network Many-Body Wavefunction Reconstruction
Implementation of G. E. Hinton and R. R. Salakhutdinov's Reducing the Dimensionality of Data with Neural Networks (Tensorflow)
QRBM Image Classification Template
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.
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
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