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Aug 23, 2017 - Jupyter Notebook
generative-adversarial-networks
Generative adversarial networks (GAN) are a class of generative machine learning frameworks. A GAN consists of two competing neural networks, often termed the Discriminator network and the Generator network. GANs have been shown to be powerful generative models and are able to successfully generate new data given a large enough training dataset.
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Takes a number and generates the images of those numbers. Trained on MNIST using GAN.
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Nov 13, 2018 - Jupyter Notebook
A Tensorflow-layer API Implementation of Deep Generative Models (MNIST Examples)
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Mar 26, 2019 - Python
Models for image2image tasks. PyTorch.
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Dec 23, 2019
DD2402 Advanced Individual Course in Computational Biology Project
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Nov 9, 2023 - Python
Experimenting with GANs in Tensorflow/Keras
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Jan 13, 2022 - Python
DCGAN on MNSIT data set using PyTorch - Stony Brook CSE512 Machine learning
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May 6, 2018 - Jupyter Notebook
The repository contains software library for Data Augmentation Services
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Aug 1, 2018 - Python
Generate Face Images using Generative Adversarial Networks (GAN) - Pytorch
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Sep 24, 2020 - HTML
Various Preprocessing tools for use with Generative Adversarial Networks
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Feb 2, 2017 - Python
A TensorFlow Implementation of "BEGAN: Boundary Equilibrium Generative Adversarial Networks" - (EASY to READ)
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May 22, 2018 - Python
Interface for generating 💐flowers💐 using GANs
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Oct 17, 2021 - Python
Keras framework for unsupervised learning
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Oct 22, 2023 - Python
CFG-GAN: Composite functional gradient learning of generative adversarial models
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Jul 9, 2020 - C++
Implementation of Constrained Adversarial Networks
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Mar 2, 2021 - Python
PyTorch Implementation of Deep Convolutional Generative Adversarial Networks (DCGAN)
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Aug 7, 2020 - Python
Implementation of "Testing Directed Acyclic Graph via Structural, Supervised and Generative Adversarial Learning" (JASA, 2023+)
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May 23, 2023 - Python
Generative_Image_Rotation: Using Pix2Pix cGAN to transform randomly oriented Protoplanetary Disk images into standardized face-on views for astronomical research.
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Jul 2, 2024 - Jupyter Notebook
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