Synthetic data generation for tabular data
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Updated
Jun 7, 2024 - Python
Synthetic data generation for tabular data
Seminar project Unsupervised Image-to-Image translation using GANs
State-of-the-art audio codec with 90x compression factor. Supports 44.1kHz, 24kHz, and 16kHz mono/stereo audio.
[CVPR 2020] GAN Compression: Efficient Architectures for Interactive Conditional GANs
A Fast Deep Learning Model to Upsample Low Resolution Videos to High Resolution at 30fps
Synthetic data generators for tabular and time-series data
medigan - A Python Library of Pretrained Generative Models for Medical Image Synthesis
Repositorio Ramo Machine Learning for Business Inteligence - Udec 2020-1 (Deep Learning with tensorflow)
✏️ Edit One for All: Interactive Batch Image Editing (CVPR 2024)
Simple interface to synthesize complex and highly dimensional datasets using Gretel APIs.
We well know GANs for success in the realistic image generation. However, they can be applied in tabular data generation. We will review and examine some recent papers about tabular GANs in action.
Using WGAN-gp and creating art portraits.
AttGAN: Facial Attribute Editing by Only Changing What You Want (IEEE TIP 2019)
This code sets up and trains a GAN to generate artwork images using Keras and TensorFlow, defining and compiling discriminator and generator networks, and saving results.
The repository is dedicated to developing AI projects, showcasing techniques for building, analyzing, and deploying models.
contains codes of Machine Learning, Deep learning and Reinforcement learning applied in sort of scratch but mostly using this library
Package for seamless 3D terrain generation using inpainting models, GANs, DEMs, and RGB satellite imagery.
Image-to-Image Translation in PyTorch
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