Monte Carlo simulations of arbitrary Ising models using RBMs.
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Updated
Feb 25, 2018 - Python
Monte Carlo simulations of arbitrary Ising models using RBMs.
Acoustic instrument / sound classification using Fast Fourier Transform, Mel Spectrograms to convert sound files to images for input into Deep Learning models for classification. Models include Restricted Boltzmann Machines, Convolutional Neural Networks, and Inception Architectures
RBM for collaborative filtering using metadata
A Deep Learning framework to model the stochastic process of time series.
Use TensorFlow to Generate Music with a Restricted Boltzmann Machine.
A web app for training and analysing Deep Belief Networks
hebbian learning for sequential generation
Machine learning applications
Solved assignments for Deep Learning course @ Faculty of Electrical Engineering and Computing, University of Zagreb
Code for the analysis conducted in the paper "On the Importance of Hidden Bias and Hidden Entropy in Representational Efficiency of the Gaussian-Bipolar Restricted Boltzmann Machines"
Application of Restricted Boltzmann Machines in building a recommender system which predicts binary ratings of movies ( 1 -> Liked, 0 -> Disliked )
Practical works on Bayesian classification, Hidden Markov Models and Restricted Boltzmann Machines
projects of all sorts of neural network
A simple implementation of a Restricted Boltzmann Machine, able to perfrom a supervised classification task on the MNIST database of handwritten digits, coded for prof. Bortolozzi course Biological Physics @unipd
To predict if a customer will like a movie or not depending on his past ratings and preferences using RBMs.
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.
Numpy implementation of Restricted Boltzmann Machine.
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