Adrian Millea - academic website

Code used in arXiv:1808.08630

From Markov Fields to Deep Belief Networks theory and experimentation on Google Landmark Recognition.

Implementation of Restricted Boltzman Machine using Python

This portfolio contains projects, course, and code for my deep learning practices

Machine Learning Basics: Artificial Neural Networks, Generative Modeling, Boltzmann Machines, GANs

Algoritmos utilizados para redução de dimensionalidade de bases de dados

A PyTorch Lightning reimplementation of "Bidirectional Helmholtz Machines" (Bornschein et al., 2016)

Deep Learning codes

Code used in paper "Deep Learning Moment Closure Approximations using Dynamic Boltzmann Distributions" arXiv 1905.12122

Basic techniques, methods and properties of Artificial Neural Networks and Deep Learning

Collection of modern tools and machine learning techniques for data analysis and application in some exercises.

Tools for Ising modeling + entropy analysis

Personal notes for probabilistic modelling reasoning course (University of Edinburgh 2017-1)

My Deep Learning and Machine Learning projects

Predict likes , dislikes as well as rating of movies to users

Dynamic Boltzmann Machine for Lattice Chemical Kinetics

Restricted Boltzmann Machine Creation as Recommendation System for Movie Review

We use Restricted Boltzmann machines to build a 1-0 recommender system for movies.

Code and reports from two projects; Boltzmann machine trained on the MNIST data and temporal difference learning model for navigating Morris water-maze task