A Great Collection of Deep Learning Tutorials and Repositories
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Updated
Jun 12, 2024
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.
A Great Collection of Deep Learning Tutorials and Repositories
HyMPS will be a platform-indipendent software suite for advanced audio/video contents production.
Generate Art
The collection of pre-trained, state-of-the-art AI models for ailia SDK
Synthetic data generation for tabular data
Revolutionary image domain translator, implemented and modified the proposed architecture in CycleGAN paper, modifications made the model suitable to accomplish extreme geometric transformations, ie from a cat to human and vice versa.
it is my take on understanding GAN architecture
A Deep Learning Classification Framework with Spectral and Spatial Feature Fusion Layers for Hyperspectral and Lidar Sensor Data
Generating aerial flood prediction imagery with generative adversarial networks
Implementation of DeepMind's Deep Generative Model of Radar (DGMR) https://arxiv.org/abs/2104.00954
Artificial Intelligence
so-vits-svc fork with realtime support, improved interface and more features.
Сustom torch style machine learning framework with automatic differentiation implemented on numpy, allows build GANs, VAEs, etc.
List of molecular design using Generative AI and Deep Learning
✌ CLoG: Benchmarking Continual Learning of Image Generation Models
🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022
12 Weeks, 24 Lessons, AI for All!
Pytorch implementation of AnimeGAN for fast photo animation
Released June 10, 2014