Utils and Notebooks for building deep-learing model with superpaper
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Updated
Jun 14, 2020 - Jupyter Notebook
Utils and Notebooks for building deep-learing model with superpaper
Pixel Sorting algorithm implemented in Python with NumPy.
This library contains executable notebooks (colab) with a Generative Art of Deep Neural Networks
A simple jupyter notebook that will help you fine tune your own Instruct Pix2Pix Stable Diffusion model.
An AI algorithm to stylize one image with another. Repository consists of two notebooks: basic NST implementation from scratch and Fast-NST pre-defined sample code for comparison.
This repository contains notebooks showcasing various generative models, including DCGAN and VAE for anime face generation, an Autoencoder for converting photos to sketches, a captioning model using an attention mechanism for an image caption generator, and more.
A collection of Haskell examples / experiments written as IHaskell notebooks.
Notebook for running Stable Diffusion – the Generative AI alternative to Dall-E and Midjourney – on IPUs
Gen AI uses GANs to generate CIFAR-10-like images. The custom GAN model comprises a Generator and a Discriminator. Users can train the model and generate images using Jupyter Notebooks or Google Colab.
Colab notebooks for GAN tutorials.
🎨 An authorial set of fundamental Python recipes on Creative Coding and Computer Art.
Artistic visualization of vector fields created with Matplotlib and Jupyter Notebook
An IPython notebook explaining the concepts of Variational Autoencoders and building one using Keras to generate new faces.
A curated list of awesome Diffusion notebooks, tools, software, tutorials and resources.
Start here
Multiple notebooks which allow the use of various machine learning methods to generate or modify multimedia content
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