# Successive Training of a Generative Adversarial Network for the Design of an Optical Cloak

arXiv: https://arxiv.org/abs/2005.08832 · HTML: https://mlsanity.com/paper/2005.08832/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 May 2020.

## Built on by (most cited first, 1 of 1)

- [Topology Optimization via Machine Learning and Deep Learning: A Review](https://mlsanity.com/paper/2210.10782/) (2022)

## Abstract (arXiv)

We present an optimization algorithm based on a deep convolution generative adversarial network (DCGAN) to design a 2-Dimensional optical cloak. The optical cloak consists in a shell of uniform and isotropical dielectric material, and the cloaking is achieved via the geometry of the shell. We use a feedback loop from the solutions of the DCGAN to successively retrain it and improve its ability to predict and find optimal geometries.