Machine Learning Methods
Chairs: Sungwook Hong (University of Seoul) and Cris Sabiu (Yonsei)
- David Parkinson (KASI) — ''Segmentation and identification for radio continuum images: complexity and the background''
- Boon Kiat Oh (SNU) — ''Machine-assisted Semi-simulation Model (MSSM): Estimating Galactic Baryonic Properties from their Dark Matter using Machine Trained on Hydrodynamical Simulation''
- Seungwoo Ha (UNIST) — ''Analysis of simulated Large Scale Structure of the universe data with deep learning''
Discussion between SKA scientists and those with machine learning experience.
- What do you expect from Machine Learning?
- How can ML help with SKA science?
- Can ML help in Data Reduction, cleaning etc?
- What are the unique challenges face considering the size and complexity of SKA data and can ML / Big Data Analytic methods help?