collection of presentations during the Carl-Zeiss-Stiftung Summerschool on Scientific Machine Learning for Astrophysics 2023
- Success and failure of ML in gravitational wave by Kaze Wong
- Scientific computing and machine learning in JAX by Patrick Kidger
- A primer on neural ODEs by Patrick Kidger
- Generalizing Scientific Machine Learning through Differentiable Simulation and SciML by Chris Rackauckas
- Information field theory by Torsten Enßlin
- Reasoning with structure: Graph Neural Networks by Andreea Deac
- Introduction to diffusion models for astrophysical applications by Laurence Perreault-Levasseur
Please cite/acknowledge the author of these documents if you find them useful.