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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.
Here are 253 public repositories matching this topic...
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
Implementation of DCGAN in Pytorch
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Apr 4, 2020 - Jupyter Notebook
Generate Face Images using Generative Adversarial Networks (GAN) - Pytorch
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Sep 24, 2020 - HTML
Implementation of my research project 'Conditional Generaton of Aerial Images for Imbalanced Learning using Generative Adversarial Networks'.
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Jun 6, 2022 - Python
DGCIT: Double Generative Adversarial Networks for Conditional Independence Testing (JMLR, 2021)
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Jan 19, 2022 - Python
Uses generative adversarial networks to create images of faces
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Aug 14, 2018 - 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
Implementation of VideoGigaGAN, SOTA video upsampling out of Adobe AI labs, in Pytorch
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May 11, 2024 - 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
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