Сustom torch style machine learning framework with automatic differentiation implemented on numpy, allows build GANs, VAEs, etc.
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Updated
Jun 8, 2024 - Python
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.
Сustom torch style machine learning framework with automatic differentiation implemented on numpy, allows build GANs, VAEs, etc.
Implementation of a WGAN-GP on the CelebA dataset with PyTorch for face generation
Generating aerial flood prediction imagery with generative adversarial networks
12 Weeks, 24 Lessons, AI for All!
Main folder. Material related to my books on synthetic data and generative AI. Also contains documents blending components from several folders, or covering topics spanning across multiple folders..
Just some notebooks I wrote to research some fun stuff in hobby time
A Great Collection of Deep Learning Tutorials and Repositories
Repo for all the SRIP 2024 work at CVIG Lab IITGN under Prof. Shanmuganathan Raman
Synthetic data generation for tabular data
✌ CLoG: Benchmarking Continual Learning of Image Generation Models
📦 GAN-based models to flash-simulate the LHCb PID detectors
Data reconstruction framework with GANs
Repository relating to the Coursera Course Generative Adversarial Networks
List of datasets and papers in X-ray security images (Computer vision/Machine Learning)
Official implemention for Diffusion Models Are Innate One-Step Generators
HyMPS will be a platform-indipendent software suite for advanced audio/video contents production.
An AI for Music Generation
Artificial Intelligence
Released June 10, 2014