Collection of generative models, e.g. GAN, VAE in NNabla
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Updated
Jul 2, 2017 - Jupyter Notebook
Collection of generative models, e.g. GAN, VAE in NNabla
Implementation of generative models
An Implementation of Restricted Boltzmann Machine with Pytorch
Unofficial implementation of StyleGan2 paper
A Sample application demonstrating how a CSRF hack can be conducted and how it can be stopped
Autoencoders in PyTorch
SUTD 2021 50.007 Machine Learning HMM 1D Design Project
Artificial Intelligence course (3rd year, 1st semester)
LSTM-Based Music Generator
Autoencoders are mostly used for different purposes such as denoising, compression data, anomaly detection, generating new data from the input data entering to the model, and more. This repository introduces a simple autoencoder architecture with some brief explanations of encoder, bottleneck and decoder parts.
A collection of resources and papers on generative compression (including neural image/video/audio compression, generation-based image/video/audio compression)
Creating NFTs with the help of generative models
Model Business Logic Cards to support responsible AI/LLM usage
Gibbs samplers for inferring latent variables and learning the parameters of Bayesian hierarchical models.
Repository of the paper Compressing Sensor Data for Remote Assistance of Autonomous Vehicles using Deep Generative Models at ML4AD @ NeurIPS 2021.
Pytorch implementation of Variational Auto-encoders with CNN; VAE with CNN
Face image generation using text input
Listing my favorite research papers 📝 from different fields as I read them.
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