A Generative Adversarial Network (GAN) written entirely in c#
-
Updated
Apr 15, 2024 - C#
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 Generative Adversarial Network (GAN) written entirely in c#
A Sample application demonstrating how a CSRF hack can be conducted and how it can be stopped
A (failed) first attempt at a chess neural network
A chess AI which uses stochastic descent through a GAN architecture. (Superseded by StochChess)
Este repositorio contiene la implementación de un agente de Conducción Autónoma basado en Deep Learning y de un sistema de generación de circuitos aleatorios con mapas de Kohonen.
Released June 10, 2014