Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
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Updated
Mar 24, 2024 - Python
Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
Boltzmann Machines in TensorFlow with examples
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…
Always sparse. Never dense. But never say never. A Sparse Training repository for the Adaptive Sparse Connectivity concept and its algorithmic instantiation, i.e. Sparse Evolutionary Training, to boost Deep Learning scalability on various aspects (e.g. memory and computational time efficiency, representation and generalization power).
Restricted Boltzmann Machines (RBMs) in PyTorch
This repository has implementation and tutorial for Deep Belief Network
Neural Network Many-Body Wavefunction Reconstruction
The goal of this project is to solve the task of name transcription from handwriting images implementing a NN approach.
A Movie Recommender System using Restricted Boltzmann Machine (RBM), approach used is collaborative filtering.
Simple code tutorial for deep belief network (DBN)
Implementation of Restricted Boltzmann Machine (RBM) and its variants in Tensorflow
Implementations of (Deep Learning + Machine Learning) Algorithms
Deep Learning Models implemented in python.
RBM implemented with spiking neurons in Python. Contrastive Divergence used to train the network.
This repository contains all the projects and labs I worked on while pursuing professional certificate programs, specializations, and bootcamp. [Areas: Deep Learning, Machine Learning, Applied Data Science].
An implementation of Restricted Boltzmann Machine in Pytorch
Tensorflow Implementation of RBM
Recommend movies to users by RBMs, TruncatedSVD, Stochastic SVD and Variational Inference
Fill missing values in Pandas DataFrames using Restricted Boltzmann Machines
Implementation of G. E. Hinton and R. R. Salakhutdinov's Reducing the Dimensionality of Data with Neural Networks (Tensorflow)
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