Square Kilometre Array: Mock-observations via generative deep learning
Description
In this project we use generative deep learning methods (GANs and VAEs) to produce realistic astronomical mock-observations of numerically simulated astrophysical objects, as they will be obseved by the Square Kilometre Array Telescope (SKA). This project contributes to the Swiss-wide activities for SKA of the SKACH Consortium.
Key Data
Projectlead
Deputy Projectlead
Project team
Project partners
Ecole polytechnique fédérale de Lausanne EPFL; Universität Zürich; Eidgenössische Technische Hochschule Zürich ETH; Fachhochschule Nordwestschweiz FHNW; Universität Basel; Haute école spécialisée de Suisse occidentale HES-SO
Project status
ongoing, started 09/2021
Funding partner
Staatssekretariat für Bildung, Forschung und Innovation SBFI
Project budget
240'000 CHF
