so-vits-svc fork with realtime support, improved interface and more features.
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Updated
May 23, 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.
so-vits-svc fork with realtime support, improved interface and more features.
HyMPS will be a platform-indipendent software suite for advanced audio/video contents production.
The collection of pre-trained, state-of-the-art AI models for ailia SDK
This repository showcases two approaches to the coulourization task of CIFAR10 images: Auto Encoder U-Nets and Deep Conditional Generative Adversarial Networks (DCGANs).
Machine learning algorithm that can create an image from a collection of photographs.
This repository showcases one of the most relevant generative models (built in pytorch) as of July 2023, Generative Adversarial Networks, for the generation of Simpson Faces.
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.
Synthetic data generation for tabular data
Generative AI Image Toolset with GANs and Diffusion for Real-World Applications
A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convol…
Pure C 3D Hybrid GAN using Cross attention, attention and convolution
Synthetic data generators for tabular and time-series data
Repo for all the SRIP 2024 work at CVIG Lab IITGN under Prof. Shanmuganathan Raman
Thesis "Development of domain adaptation methods for generative models"
Generative models nano version for fun. No STOA here, nano first.
Data reconstruction framework with GANs
A Great Collection of Deep Learning Tutorials and Repositories
TRGAN: A Time-Dependent Generative Adversarial Network for Synthetic Transactional Data Generation
Released June 10, 2014